From 13b8591af8a5a6d8be1c34f586609430e09e5729 Mon Sep 17 00:00:00 2001 From: chentong319 Date: Tue, 14 Jul 2020 11:15:06 -0400 Subject: [PATCH] add AnyMemRef (#219) --- docs/Dialects/onnx.md | 874 ++++++++++++++++---------------- src/Dialect/ONNX/ONNXOps.td.inc | 874 ++++++++++++++++---------------- utils/gen_onnx_mlir.py | 3 + 3 files changed, 877 insertions(+), 874 deletions(-) diff --git a/docs/Dialects/onnx.md b/docs/Dialects/onnx.md index f1c5d6e..63e5277 100644 --- a/docs/Dialects/onnx.md +++ b/docs/Dialects/onnx.md @@ -11,13 +11,13 @@ ONNX Abs operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Acos` (ONNXAcosOp) @@ -29,13 +29,13 @@ ONNX Acos operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Acosh` (ONNXAcoshOp) @@ -47,13 +47,13 @@ ONNX Acosh operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Add` (ONNXAddOp) @@ -67,14 +67,14 @@ ONNX Add operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.And` (ONNXAndOp) @@ -89,14 +89,14 @@ ONNX And operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 1-bit signless integer values -`B` | tensor of 1-bit signless integer values +`A` | tensor of 1-bit signless integer values or memref of any type values +`B` | tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 1-bit signless integer values +`C` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.ArgMax` (ONNXArgMaxOp) @@ -118,7 +118,7 @@ ONNX ArgMax operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: @@ -146,7 +146,7 @@ ONNX ArgMin operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: @@ -165,14 +165,14 @@ ONNX ArrayFeatureExtractor operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or tensor of stirng type values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or tensor of stirng type values or memref of any type values `Y` | tensor of 64-bit signless integer values #### Results: | Result | Description | | :----: | ----------- | -`Z` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or tensor of stirng type values +`Z` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or tensor of stirng type values or memref of any type values ### `onnx.Asin` (ONNXAsinOp) @@ -184,13 +184,13 @@ ONNX Asin operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Asinh` (ONNXAsinhOp) @@ -202,13 +202,13 @@ ONNX Asinh operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Atan` (ONNXAtanOp) @@ -220,13 +220,13 @@ ONNX Atan operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Atanh` (ONNXAtanhOp) @@ -238,13 +238,13 @@ ONNX Atanh operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.AveragePool` (ONNXAveragePoolOp) @@ -295,13 +295,13 @@ ONNX AveragePool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.BatchNormalization` (ONNXBatchNormalizationOp) @@ -329,21 +329,21 @@ ONNX BatchNormalization operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`scale` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`var` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`scale` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`var` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`out_mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type -`out_var` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type -`saved_mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type -`saved_var` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`out_mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type +`out_var` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type +`saved_mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type +`saved_var` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type ### `onnx.BatchNormalizationTestMode` (ONNXBatchNormalizationTestModeOp) @@ -399,13 +399,13 @@ ONNX Binarizer operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`Y` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values ### `onnx.BitShift` (ONNXBitShiftOp) @@ -434,14 +434,14 @@ ONNX BitShift operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or memref of any type values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Z` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values +`Z` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or memref of any type values ### `onnx.CastMap` (ONNXCastMapOp) @@ -463,13 +463,13 @@ ONNX CastMap operation | Operand | Description | | :-----: | ----------- | -`X` | tuple with any combination of 64-bit signless integer or stirng type values or tuple with any combination of 64-bit signless integer or 32-bit float values +`X` | tuple with any combination of 64-bit signless integer or stirng type values or tuple with any combination of 64-bit signless integer or 32-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of stirng type values or tensor of 32-bit float values or tensor of 64-bit signless integer values +`Y` | tensor of stirng type values or tensor of 32-bit float values or tensor of 64-bit signless integer values or memref of any type values ### `onnx.Cast` (ONNXCastOp) @@ -505,13 +505,13 @@ ONNX Cast operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or tensor of stirng type values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or tensor of stirng type values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or tensor of stirng type values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or tensor of stirng type values or memref of any type values ### `onnx.CategoryMapper` (ONNXCategoryMapperOp) @@ -539,13 +539,13 @@ ONNX CategoryMapper operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of stirng type values or tensor of 64-bit signless integer values +`X` | tensor of stirng type values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of stirng type values or tensor of 64-bit signless integer values +`Y` | tensor of stirng type values or tensor of 64-bit signless integer values or memref of any type values ### `onnx.Ceil` (ONNXCeilOp) @@ -559,13 +559,13 @@ ONNX Ceil operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Clip` (ONNXClipOp) @@ -579,15 +579,15 @@ ONNX Clip operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`min` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type -`max` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`min` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type +`max` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type ### `onnx.Compress` (ONNXCompressOp) @@ -608,14 +608,14 @@ ONNX Compress operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`condition` | tensor of 1-bit signless integer values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`condition` | tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.ConcatFromSequence` (ONNXConcatFromSequenceOp) @@ -637,13 +637,13 @@ ONNX ConcatFromSequence operation | Operand | Description | | :-----: | ----------- | -`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`concat_result` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`concat_result` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Concat` (ONNXConcatOp) @@ -661,13 +661,13 @@ ONNX Concat operation | Operand | Description | | :-----: | ----------- | -`inputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`inputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`concat_result` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`concat_result` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.ConstantOfShape` (ONNXConstantOfShapeOp) @@ -685,13 +685,13 @@ ONNX ConstantOfShape operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 64-bit signless integer values +`input` | tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or memref of any type values ### `onnx.Constant` (ONNXConstantOp) @@ -711,7 +711,7 @@ ONNX Constant operation | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.ConvInteger` (ONNXConvIntegerOp) @@ -735,16 +735,16 @@ ONNX ConvInteger operation | Operand | Description | | :-----: | ----------- | -`x` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`w` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`x_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or none type -`w_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or none type +`x` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`w` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`x_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values or none type +`w_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`y` | tensor of 32-bit signless integer values +`y` | tensor of 32-bit signless integer values or memref of any type values ### `onnx.Conv` (ONNXConvOp) @@ -768,15 +768,15 @@ ONNX Conv operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type ### `onnx.ConvTranspose` (ONNXConvTransposeOp) @@ -814,15 +814,15 @@ ONNX ConvTranspose operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type ### `onnx.Cos` (ONNXCosOp) @@ -834,13 +834,13 @@ ONNX Cos operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Cosh` (ONNXCoshOp) @@ -852,13 +852,13 @@ ONNX Cosh operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.CumSum` (ONNXCumSumOp) @@ -896,14 +896,14 @@ ONNX CumSum operation | Operand | Description | | :-----: | ----------- | -`x` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values -`axis` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`x` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`axis` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`y` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values +`y` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.DepthToSpace` (ONNXDepthToSpaceOp) @@ -948,13 +948,13 @@ ONNX DepthToSpace operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.DequantizeLinear` (ONNXDequantizeLinearOp) @@ -969,9 +969,9 @@ ONNX DequantizeLinear operation | Operand | Description | | :-----: | ----------- | -`x` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 32-bit signless integer values +`x` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 32-bit signless integer values or memref of any type values `x_scale` | tensor of 32-bit float values -`x_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 32-bit signless integer values or none type +`x_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 32-bit signless integer values or memref of any type values or none type #### Results: @@ -993,13 +993,13 @@ ONNX Det operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.DictVectorizer` (ONNXDictVectorizerOp) @@ -1029,13 +1029,13 @@ ONNX DictVectorizer operation | Operand | Description | | :-----: | ----------- | -`X` | tuple with any combination of stirng type or 64-bit signless integer values or tuple with any combination of 64-bit signless integer or stirng type values or tuple with any combination of 64-bit signless integer or 32-bit float values or tuple with any combination of 64-bit signless integer or 64-bit float values or tuple with any combination of stirng type or 32-bit float values or tuple with any combination of stirng type or 64-bit float values +`X` | tuple with any combination of stirng type or 64-bit signless integer values or tuple with any combination of 64-bit signless integer or stirng type values or tuple with any combination of 64-bit signless integer or 32-bit float values or tuple with any combination of 64-bit signless integer or 64-bit float values or tuple with any combination of stirng type or 32-bit float values or tuple with any combination of stirng type or 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values +`Y` | tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or memref of any type values ### `onnx.Div` (ONNXDivOp) @@ -1049,14 +1049,14 @@ ONNX Div operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Dropout` (ONNXDropoutOp) @@ -1079,14 +1079,14 @@ ONNX Dropout operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`mask` | tensor of 1-bit signless integer values or none type +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`mask` | tensor of 1-bit signless integer values or memref of any type values or none type ### `onnx.DynamicQuantizeLinear` (ONNXDynamicQuantizeLinearOp) @@ -1119,15 +1119,15 @@ ONNX DynamicQuantizeLinear operation | Operand | Description | | :-----: | ----------- | -`x` | tensor of 32-bit float values +`x` | tensor of 32-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`y` | tensor of 8-bit unsigned integer values +`y` | tensor of 8-bit unsigned integer values or memref of any type values `y_scale` | tensor of 32-bit float values -`y_zero_point` | tensor of 8-bit unsigned integer values +`y_zero_point` | tensor of 8-bit unsigned integer values or memref of any type values ### `onnx.Elu` (ONNXEluOp) @@ -1148,13 +1148,13 @@ ONNX Elu operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.EntryPoint` (ONNXEntryPointOp) @@ -1175,14 +1175,14 @@ ONNX Equal operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 1-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 1-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 1-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 1-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 1-bit signless integer values +`C` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.Erf` (ONNXErfOp) @@ -1194,13 +1194,13 @@ ONNX Erf operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Exp` (ONNXExpOp) @@ -1212,13 +1212,13 @@ ONNX Exp operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Expand` (ONNXExpandOp) @@ -1237,14 +1237,14 @@ ONNX Expand operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `shape` | tensor of 64-bit signless integer values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.EyeLike` (ONNXEyeLikeOp) @@ -1269,13 +1269,13 @@ ONNX EyeLike operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 1-bit signless integer values or memref of any type values ### `onnx.FeatureVectorizer` (ONNXFeatureVectorizerOp) @@ -1296,7 +1296,7 @@ ONNX FeatureVectorizer operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: @@ -1322,13 +1322,13 @@ ONNX Flatten operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Floor` (ONNXFloorOp) @@ -1342,13 +1342,13 @@ ONNX Floor operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.GRU` (ONNXGRUOp) @@ -1444,19 +1444,19 @@ ONNX GRU operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`R` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type -`sequence_lens` | tensor of 32-bit signless integer values or none type -`initial_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`R` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type +`sequence_lens` | tensor of 32-bit signless integer values or memref of any type values or none type +`initial_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type -`Y_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type +`Y_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type ### `onnx.GatherElements` (ONNXGatherElementsOp) @@ -1528,14 +1528,14 @@ ONNX GatherElements operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.GatherND` (ONNXGatherNDOp) @@ -1611,14 +1611,14 @@ ONNX GatherND operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `indices` | tensor of 64-bit signless integer values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Gather` (ONNXGatherOp) @@ -1692,14 +1692,14 @@ ONNX Gather operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Gemm` (ONNXGemmOp) @@ -1732,15 +1732,15 @@ ONNX Gemm operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`C` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type +`A` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`C` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type ### `onnx.GlobalAveragePool` (ONNXGlobalAveragePoolOp) @@ -1754,13 +1754,13 @@ ONNX GlobalAveragePool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.GlobalLpPool` (ONNXGlobalLpPoolOp) @@ -1780,13 +1780,13 @@ ONNX GlobalLpPool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.GlobalMaxPool` (ONNXGlobalMaxPoolOp) @@ -1800,13 +1800,13 @@ ONNX GlobalMaxPool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Greater` (ONNXGreaterOp) @@ -1821,14 +1821,14 @@ ONNX Greater operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 1-bit signless integer values +`C` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.HardSigmoid` (ONNXHardSigmoidOp) @@ -1849,13 +1849,13 @@ ONNX HardSigmoid operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Hardmax` (ONNXHardmaxOp) @@ -1886,13 +1886,13 @@ ONNX Hardmax operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Identity` (ONNXIdentityOp) @@ -1904,13 +1904,13 @@ ONNX Identity operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.If` (ONNXIfOp) @@ -1929,13 +1929,13 @@ ONNX If operation | Operand | Description | | :-----: | ----------- | -`cond` | tensor of 1-bit signless integer values +`cond` | tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Imputer` (ONNXImputerOp) @@ -1963,13 +1963,13 @@ ONNX Imputer operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`Y` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values ### `onnx.InstanceNormalization` (ONNXInstanceNormalizationOp) @@ -1992,15 +1992,15 @@ ONNX InstanceNormalization operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`scale` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`scale` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.IsInf` (ONNXIsInfOp) @@ -2019,13 +2019,13 @@ ONNX IsInf operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 1-bit signless integer values +`Y` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.IsNaN` (ONNXIsNaNOp) @@ -2037,13 +2037,13 @@ ONNX IsNaN operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 1-bit signless integer values +`Y` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.LRN` (ONNXLRNOp) @@ -2073,13 +2073,13 @@ ONNX LRN operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.LSTM` (ONNXLSTMOp) @@ -2183,22 +2183,22 @@ ONNX LSTM operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`R` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type -`sequence_lens` | tensor of 32-bit signless integer values or none type -`initial_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type -`initial_c` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type -`P` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`R` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type +`sequence_lens` | tensor of 32-bit signless integer values or memref of any type values or none type +`initial_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type +`initial_c` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type +`P` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type or none type -`Y_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type or none type or none type -`Y_c` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type or none type or none type or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type or none type +`Y_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type or none type or none type +`Y_c` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type or none type or none type or none type ### `onnx.LabelEncoder` (ONNXLabelEncoderOp) @@ -2240,13 +2240,13 @@ ONNX LabelEncoder operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of stirng type values or tensor of 64-bit signless integer values or tensor of 32-bit float values +`X` | tensor of stirng type values or tensor of 64-bit signless integer values or tensor of 32-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of stirng type values or tensor of 64-bit signless integer values or tensor of 32-bit float values +`Y` | tensor of stirng type values or tensor of 64-bit signless integer values or tensor of 32-bit float values or memref of any type values ### `onnx.LeakyRelu` (ONNXLeakyReluOp) @@ -2266,13 +2266,13 @@ ONNX LeakyRelu operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Less` (ONNXLessOp) @@ -2287,14 +2287,14 @@ ONNX Less operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 1-bit signless integer values +`C` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.LinearClassifier` (ONNXLinearClassifierOp) @@ -2317,13 +2317,13 @@ ONNX LinearClassifier operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of stirng type values or tensor of 64-bit signless integer values +`Y` | tensor of stirng type values or tensor of 64-bit signless integer values or memref of any type values `Z` | tensor of 32-bit float values ### `onnx.LinearRegressor` (ONNXLinearRegressorOp) @@ -2350,7 +2350,7 @@ ONNX LinearRegressor operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: @@ -2368,13 +2368,13 @@ ONNX Log operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.LogSoftmax` (ONNXLogSoftmaxOp) @@ -2405,13 +2405,13 @@ ONNX LogSoftmax operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Loop` (ONNXLoopOp) @@ -2541,15 +2541,15 @@ ONNX Loop operation | Operand | Description | | :-----: | ----------- | -`M` | tensor of 64-bit signless integer values or none type -`cond` | tensor of 1-bit signless integer values or none type -`v_initial` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`M` | tensor of 64-bit signless integer values or memref of any type values or none type +`cond` | tensor of 1-bit signless integer values or memref of any type values or none type +`v_initial` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`v_final_and_scan_outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`v_final_and_scan_outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.LpNormalization` (ONNXLpNormalizationOp) @@ -2568,13 +2568,13 @@ ONNX LpNormalization operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.LpPool` (ONNXLpPoolOp) @@ -2600,13 +2600,13 @@ ONNX LpPool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.MatMulInteger` (ONNXMatMulIntegerOp) @@ -2619,16 +2619,16 @@ ONNX MatMulInteger operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`B` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`a_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or none type -`b_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or none type +`A` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`B` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`a_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values or none type +`b_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 32-bit signless integer values +`Y` | tensor of 32-bit signless integer values or memref of any type values ### `onnx.MatMul` (ONNXMatMulOp) @@ -2640,14 +2640,14 @@ ONNX MatMul operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`A` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values ### `onnx.Max` (ONNXMaxOp) @@ -2661,13 +2661,13 @@ ONNX Max operation | Operand | Description | | :-----: | ----------- | -`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`max` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`max` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.MaxPool` (ONNXMaxPoolOp) @@ -2719,14 +2719,14 @@ ONNX MaxPool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`Indices` | tensor of 64-bit signless integer values or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`Indices` | tensor of 64-bit signless integer values or memref of any type values or none type ### `onnx.MaxPoolSingleOut` (ONNXMaxPoolSingleOutOp) @@ -2778,14 +2778,14 @@ ONNX MaxRoiPool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`rois` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`rois` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.MaxUnpool` (ONNXMaxUnpoolOp) @@ -2822,15 +2822,15 @@ ONNX MaxUnpool operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`I` | tensor of 64-bit signless integer values -`output_shape` | tensor of 64-bit signless integer values or none type +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`I` | tensor of 64-bit signless integer values or memref of any type values +`output_shape` | tensor of 64-bit signless integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Mean` (ONNXMeanOp) @@ -2844,13 +2844,13 @@ ONNX Mean operation | Operand | Description | | :-----: | ----------- | -`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`mean` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.MeanVarianceNormalization` (ONNXMeanVarianceNormalizationOp) @@ -2869,13 +2869,13 @@ ONNX MeanVarianceNormalization operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Min` (ONNXMinOp) @@ -2889,13 +2889,13 @@ ONNX Min operation | Operand | Description | | :-----: | ----------- | -`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`min` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`min` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Mod` (ONNXModOp) @@ -2925,14 +2925,14 @@ ONNX Mod operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`C` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Mul` (ONNXMulOp) @@ -2946,14 +2946,14 @@ ONNX Mul operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Multinomial` (ONNXMultinomialOp) @@ -2974,13 +2974,13 @@ ONNX Multinomial operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`output` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values ### `onnx.Neg` (ONNXNegOp) @@ -2994,13 +2994,13 @@ ONNX Neg operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 32-bit signless integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 64-bit float values +`X` | tensor of 32-bit float values or tensor of 32-bit signless integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 32-bit float values or tensor of 32-bit signless integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 64-bit float values +`Y` | tensor of 32-bit float values or tensor of 32-bit signless integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.NonMaxSuppression` (ONNXNonMaxSuppressionOp) @@ -3049,7 +3049,7 @@ ONNX NonZero operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: @@ -3082,7 +3082,7 @@ ONNX Normalizer operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: @@ -3100,13 +3100,13 @@ ONNX Not operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 1-bit signless integer values +`X` | tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 1-bit signless integer values +`Y` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.OneHotEncoder` (ONNXOneHotEncoderOp) @@ -3133,7 +3133,7 @@ ONNX OneHotEncoder operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of stirng type values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of stirng type values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: @@ -3175,15 +3175,15 @@ ONNX OneHot operation | Operand | Description | | :-----: | ----------- | -`indices` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`depth` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`values` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`indices` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`depth` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`values` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Or` (ONNXOrOp) @@ -3198,14 +3198,14 @@ ONNX Or operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 1-bit signless integer values -`B` | tensor of 1-bit signless integer values +`A` | tensor of 1-bit signless integer values or memref of any type values +`B` | tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 1-bit signless integer values +`C` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.PRelu` (ONNXPReluOp) @@ -3220,14 +3220,14 @@ ONNX PRelu operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`slope` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`slope` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values ### `onnx.PadConstantPad` (ONNXPadConstantPadOp) @@ -3411,15 +3411,15 @@ ONNX Pad operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values `pads` | tensor of 64-bit signless integer values or none type -`constant_value` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type +`constant_value` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type ### `onnx.Pow` (ONNXPowOp) @@ -3434,14 +3434,14 @@ ONNX Pow operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Z` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Z` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.QLinearConv` (ONNXQLinearConvOp) @@ -3468,21 +3468,21 @@ ONNX QLinearConv operation | Operand | Description | | :-----: | ----------- | -`x` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`x` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values `x_scale` | tensor of 32-bit float values -`x_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`w` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`x_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`w` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values `w_scale` | tensor of 32-bit float values -`w_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`w_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values `y_scale` | tensor of 32-bit float values -`y_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`B` | tensor of 32-bit signless integer values or none type +`y_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`B` | tensor of 32-bit signless integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`y` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`y` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values ### `onnx.QLinearMatMul` (ONNXQLinearMatMulOp) @@ -3501,20 +3501,20 @@ ONNX QLinearMatMul operation | Operand | Description | | :-----: | ----------- | -`a` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`a` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values `a_scale` | tensor of 32-bit float values -`a_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values -`b` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`a_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values +`b` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values `b_scale` | tensor of 32-bit float values -`b_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`b_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values `y_scale` | tensor of 32-bit float values -`y_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`y_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`y` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values +`y` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values ### `onnx.QuantizeLinear` (ONNXQuantizeLinearOp) @@ -3528,15 +3528,15 @@ ONNX QuantizeLinear operation | Operand | Description | | :-----: | ----------- | -`x` | tensor of 32-bit float values or tensor of 32-bit signless integer values +`x` | tensor of 32-bit float values or tensor of 32-bit signless integer values or memref of any type values `y_scale` | tensor of 32-bit float values -`y_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or none type +`y_zero_point` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`y` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or none type +`y` | tensor of 8-bit signless integer values or tensor of 8-bit unsigned integer values or memref of any type values or none type ### `onnx.RNN` (ONNXRNNOp) @@ -3619,19 +3619,19 @@ ONNX RNN operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`R` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type -`sequence_lens` | tensor of 32-bit signless integer values or none type -`initial_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`W` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`R` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type +`sequence_lens` | tensor of 32-bit signless integer values or memref of any type values or none type +`initial_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type -`Y_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or none type or none type or none type or none type +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type +`Y_h` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values or none type or none type or none type or none type ### `onnx.RandomNormalLike` (ONNXRandomNormalLikeOp) @@ -3658,13 +3658,13 @@ ONNX RandomNormalLike operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.RandomNormal` (ONNXRandomNormalOp) @@ -3692,7 +3692,7 @@ ONNX RandomNormal operation | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.RandomUniformLike` (ONNXRandomUniformLikeOp) @@ -3719,13 +3719,13 @@ ONNX RandomUniformLike operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.RandomUniform` (ONNXRandomUniformOp) @@ -3752,7 +3752,7 @@ ONNX RandomUniform operation | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Range` (ONNXRangeOp) @@ -3788,15 +3788,15 @@ ONNX Range operation | Operand | Description | | :-----: | ----------- | -`start` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`limit` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`delta` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`start` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`limit` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`delta` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`output` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values ### `onnx.Reciprocal` (ONNXReciprocalOp) @@ -3810,13 +3810,13 @@ ONNX Reciprocal operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceL1` (ONNXReduceL1Op) @@ -3840,13 +3840,13 @@ ONNX ReduceL1 operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceL2` (ONNXReduceL2Op) @@ -3870,13 +3870,13 @@ ONNX ReduceL2 operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceLogSumExp` (ONNXReduceLogSumExpOp) @@ -3900,13 +3900,13 @@ ONNX ReduceLogSumExp operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceLogSum` (ONNXReduceLogSumOp) @@ -3930,13 +3930,13 @@ ONNX ReduceLogSum operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceMax` (ONNXReduceMaxOp) @@ -3960,13 +3960,13 @@ ONNX ReduceMax operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceMean` (ONNXReduceMeanOp) @@ -3990,13 +3990,13 @@ ONNX ReduceMean operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceMin` (ONNXReduceMinOp) @@ -4020,13 +4020,13 @@ ONNX ReduceMin operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceProd` (ONNXReduceProdOp) @@ -4050,13 +4050,13 @@ ONNX ReduceProd operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceSum` (ONNXReduceSumOp) @@ -4080,13 +4080,13 @@ ONNX ReduceSum operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.ReduceSumSquare` (ONNXReduceSumSquareOp) @@ -4110,13 +4110,13 @@ ONNX ReduceSumSquare operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`reduced` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Relu` (ONNXReluOp) @@ -4130,13 +4130,13 @@ ONNX Relu operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Reshape` (ONNXReshapeOp) @@ -4153,14 +4153,14 @@ ONNX Reshape operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `shape` | tensor of 64-bit signless integer values or none type #### Results: | Result | Description | | :----: | ----------- | -`reshaped` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`reshaped` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Resize` (ONNXResizeOp) @@ -4185,8 +4185,8 @@ ONNX Resize operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`roi` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`roi` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values `scales` | tensor of 32-bit float values `sizes` | tensor of 64-bit signless integer values or none type @@ -4194,7 +4194,7 @@ ONNX Resize operation | Result | Description | | :----: | ----------- | -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.ReverseSequence` (ONNXReverseSequenceOp) @@ -4245,14 +4245,14 @@ ONNX ReverseSequence operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `sequence_lens` | tensor of 64-bit signless integer values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.RoiAlign` (ONNXRoiAlignOp) @@ -4284,15 +4284,15 @@ ONNX RoiAlign operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`rois` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`batch_indices` | tensor of 64-bit signless integer values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`rois` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`batch_indices` | tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Round` (ONNXRoundOp) @@ -4316,13 +4316,13 @@ ONNX Round operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.SVMClassifier` (ONNXSVMClassifierOp) @@ -4350,13 +4350,13 @@ ONNX SVMClassifier operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of stirng type values or tensor of 64-bit signless integer values +`Y` | tensor of stirng type values or tensor of 64-bit signless integer values or memref of any type values `Z` | tensor of 32-bit float values ### `onnx.SVMRegressor` (ONNXSVMRegressorOp) @@ -4382,7 +4382,7 @@ ONNX SVMRegressor operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: @@ -4407,7 +4407,7 @@ ONNX Scaler operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: @@ -4556,13 +4556,13 @@ ONNX Scan operation | Operand | Description | | :-----: | ----------- | -`initial_state_and_scan_inputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`initial_state_and_scan_inputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`final_state_and_scan_outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`final_state_and_scan_outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.ScatterElements` (ONNXScatterElementsOp) @@ -4630,15 +4630,15 @@ ONNX ScatterElements operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`updates` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`updates` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.ScatterND` (ONNXScatterNDOp) @@ -4705,15 +4705,15 @@ ONNX ScatterND operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `indices` | tensor of 64-bit signless integer values -`updates` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`updates` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Scatter` (ONNXScatterOp) @@ -4783,15 +4783,15 @@ ONNX Scatter operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`updates` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`indices` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`updates` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Selu` (ONNXSeluOp) @@ -4813,13 +4813,13 @@ ONNX Selu operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.SequenceAt` (ONNXSequenceAtOp) @@ -4833,14 +4833,14 @@ ONNX SequenceAt operation | Operand | Description | | :-----: | ----------- | -`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values -`position` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values +`position` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`tensor` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`tensor` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.SequenceConstruct` (ONNXSequenceConstructOp) @@ -4853,13 +4853,13 @@ ONNX SequenceConstruct operation | Operand | Description | | :-----: | ----------- | -`inputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`inputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values ### `onnx.SequenceEmpty` (ONNXSequenceEmptyOp) @@ -4877,7 +4877,7 @@ ONNX SequenceEmpty operation | Result | Description | | :----: | ----------- | -`output` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`output` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values ### `onnx.SequenceErase` (ONNXSequenceEraseOp) @@ -4892,14 +4892,14 @@ ONNX SequenceErase operation | Operand | Description | | :-----: | ----------- | -`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values -`position` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type +`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values +`position` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values ### `onnx.SequenceInsert` (ONNXSequenceInsertOp) @@ -4915,15 +4915,15 @@ ONNX SequenceInsert operation | Operand | Description | | :-----: | ----------- | -`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values -`tensor` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`position` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type +`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values +`tensor` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`position` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values ### `onnx.SequenceLength` (ONNXSequenceLengthOp) @@ -4935,13 +4935,13 @@ ONNX SequenceLength operation | Operand | Description | | :-----: | ----------- | -`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`input_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`length` | tensor of 64-bit signless integer values +`length` | tensor of 64-bit signless integer values or memref of any type values ### `onnx.Shape` (ONNXShapeOp) @@ -4953,13 +4953,13 @@ ONNX Shape operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`shape` | tensor of 64-bit signless integer values +`shape` | tensor of 64-bit signless integer values or memref of any type values ### `onnx.Shrink` (ONNXShrinkOp) @@ -4981,13 +4981,13 @@ ONNX Shrink operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Sigmoid` (ONNXSigmoidOp) @@ -5001,13 +5001,13 @@ ONNX Sigmoid operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Sign` (ONNXSignOp) @@ -5020,13 +5020,13 @@ ONNX Sign operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Sin` (ONNXSinOp) @@ -5038,13 +5038,13 @@ ONNX Sin operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Sinh` (ONNXSinhOp) @@ -5056,13 +5056,13 @@ ONNX Sinh operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Size` (ONNXSizeOp) @@ -5074,13 +5074,13 @@ ONNX Size operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`size` | tensor of 64-bit signless integer values +`size` | tensor of 64-bit signless integer values or memref of any type values ### `onnx.Slice` (ONNXSliceOp) @@ -5125,17 +5125,17 @@ ONNX Slice operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`starts` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`ends` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values -`axes` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type -`steps` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type or none type +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`starts` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`ends` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values +`axes` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type +`steps` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type or none type #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Softmax` (ONNXSoftmaxOp) @@ -5166,13 +5166,13 @@ ONNX Softmax operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Softplus` (ONNXSoftplusOp) @@ -5186,13 +5186,13 @@ ONNX Softplus operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Softsign` (ONNXSoftsignOp) @@ -5204,13 +5204,13 @@ ONNX Softsign operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.SpaceToDepth` (ONNXSpaceToDepthOp) @@ -5230,13 +5230,13 @@ ONNX SpaceToDepth operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Split` (ONNXSplitOp) @@ -5257,13 +5257,13 @@ ONNX Split operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`outputs` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.SplitToSequence` (ONNXSplitToSequenceOp) @@ -5291,14 +5291,14 @@ ONNX SplitToSequence operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`split` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or none type +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`split` | tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values or none type #### Results: | Result | Description | | :----: | ----------- | -`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values +`output_sequence` | tensor of tensor of 8-bit unsigned integer values values or tensor of tensor of 16-bit unsigned integer values values or tensor of tensor of 32-bit unsigned integer values values or tensor of tensor of 64-bit unsigned integer values values or tensor of tensor of 8-bit signless integer values values or tensor of tensor of 16-bit signless integer values values or tensor of tensor of 32-bit signless integer values values or tensor of tensor of 64-bit signless integer values values or tensor of tensor of 16-bit float values values or tensor of tensor of 32-bit float values values or tensor of tensor of 64-bit float values values or tensor of tensor of stirng type values values or tensor of tensor of 1-bit signless integer values values or tensor of tensor of complex type with 32-bit float elements values values or tensor of tensor of complex type with 64-bit float elements values values or memref of any type values ### `onnx.Sqrt` (ONNXSqrtOp) @@ -5312,13 +5312,13 @@ ONNX Sqrt operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Squeeze` (ONNXSqueezeOp) @@ -5339,13 +5339,13 @@ ONNX Squeeze operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`squeezed` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`squeezed` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.StringNormalizer` (ONNXStringNormalizerOp) @@ -5394,14 +5394,14 @@ ONNX Sub operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`A` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`B` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`C` | tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Sum` (ONNXSumOp) @@ -5415,13 +5415,13 @@ ONNX Sum operation | Operand | Description | | :-----: | ----------- | -`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`data_0` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`sum` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`sum` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Tan` (ONNXTanOp) @@ -5433,13 +5433,13 @@ ONNX Tan operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Tanh` (ONNXTanhOp) @@ -5451,13 +5451,13 @@ ONNX Tanh operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`input` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`output` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.TfIdfVectorizer` (ONNXTfIdfVectorizerOp) @@ -5509,13 +5509,13 @@ ONNX TfIdfVectorizer operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of stirng type values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values +`X` | tensor of stirng type values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 32-bit float values +`Y` | tensor of 32-bit float values or memref of any type values ### `onnx.ThresholdedRelu` (ONNXThresholdedReluOp) @@ -5535,13 +5535,13 @@ ONNX ThresholdedRelu operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`Y` | tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values ### `onnx.Tile` (ONNXTileOp) @@ -5555,14 +5555,14 @@ ONNX Tile operation | Operand | Description | | :-----: | ----------- | -`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`repeats` | tensor of 64-bit signless integer values +`input` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`repeats` | tensor of 64-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.TopK` (ONNXTopKOp) @@ -5595,15 +5595,15 @@ ONNX TopK operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values `K` | tensor of 64-bit signless integer values #### Results: | Result | Description | | :----: | ----------- | -`Values` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values -`Indices` | tensor of 64-bit signless integer values +`Values` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or memref of any type values +`Indices` | tensor of 64-bit signless integer values or memref of any type values ### `onnx.Transpose` (ONNXTransposeOp) @@ -5623,13 +5623,13 @@ ONNX Transpose operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`transposed` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`transposed` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.TreeEnsembleClassifier` (ONNXTreeEnsembleClassifierOp) @@ -5671,13 +5671,13 @@ ONNX TreeEnsembleClassifier operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of stirng type values or tensor of 64-bit signless integer values +`Y` | tensor of stirng type values or tensor of 64-bit signless integer values or memref of any type values `Z` | tensor of 32-bit float values ### `onnx.TreeEnsembleRegressor` (ONNXTreeEnsembleRegressorOp) @@ -5721,7 +5721,7 @@ ONNX TreeEnsembleRegressor operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values +`X` | tensor of 32-bit float values or tensor of 64-bit float values or tensor of 64-bit signless integer values or tensor of 32-bit signless integer values or memref of any type values #### Results: @@ -5820,13 +5820,13 @@ ONNX Unique operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `indices` | tensor of 64-bit signless integer values or none type `inverse_indices` | tensor of 64-bit signless integer values or none type `counts` | tensor of 64-bit signless integer values or none type @@ -5858,13 +5858,13 @@ ONNX Unsqueeze operation | Operand | Description | | :-----: | ----------- | -`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`data` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`expanded` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`expanded` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Upsample` (ONNXUpsampleOp) @@ -5884,14 +5884,14 @@ ONNX Upsample operation | Operand | Description | | :-----: | ----------- | -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values `scales` | tensor of 32-bit float values #### Results: | Result | Description | | :----: | ----------- | -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Where` (ONNXWhereOp) @@ -5906,15 +5906,15 @@ ONNX Where operation | Operand | Description | | :-----: | ----------- | -`condition` | tensor of 1-bit signless integer values -`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values -`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`condition` | tensor of 1-bit signless integer values or memref of any type values +`X` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values +`Y` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values +`output` | tensor of 8-bit unsigned integer values or tensor of 16-bit unsigned integer values or tensor of 32-bit unsigned integer values or tensor of 64-bit unsigned integer values or tensor of 8-bit signless integer values or tensor of 16-bit signless integer values or tensor of 32-bit signless integer values or tensor of 64-bit signless integer values or tensor of 16-bit float values or tensor of 32-bit float values or tensor of 64-bit float values or tensor of stirng type values or tensor of 1-bit signless integer values or tensor of complex type with 32-bit float elements values or tensor of complex type with 64-bit float elements values or memref of any type values ### `onnx.Xor` (ONNXXorOp) @@ -5929,14 +5929,14 @@ ONNX Xor operation | Operand | Description | | :-----: | ----------- | -`A` | tensor of 1-bit signless integer values -`B` | tensor of 1-bit signless integer values +`A` | tensor of 1-bit signless integer values or memref of any type values +`B` | tensor of 1-bit signless integer values or memref of any type values #### Results: | Result | Description | | :----: | ----------- | -`C` | tensor of 1-bit signless integer values +`C` | tensor of 1-bit signless integer values or memref of any type values ### `onnx.ZipMap` (ONNXZipMapOp) @@ -5964,5 +5964,5 @@ ONNX ZipMap operation | Result | Description | | :----: | ----------- | -`Z` | tensor of tuple with any combination of stirng type or 32-bit float values values or tensor of tuple with any combination of 64-bit signless integer or 32-bit float values values +`Z` | tensor of tuple with any combination of stirng type or 32-bit float values values or tensor of tuple with any combination of 64-bit signless integer or 32-bit float values values or memref of any type values diff --git a/src/Dialect/ONNX/ONNXOps.td.inc b/src/Dialect/ONNX/ONNXOps.td.inc index 7089c14..eb183cd 100644 --- a/src/Dialect/ONNX/ONNXOps.td.inc +++ b/src/Dialect/ONNX/ONNXOps.td.inc @@ -12,8 +12,8 @@ def ONNXAbsOp:ONNX_Op<"Abs", "(Tensor) where the absolute is, y = abs(x), is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value X", [{ auto elementType = X.getType().cast().getElementType(); @@ -45,8 +45,8 @@ def ONNXAcosOp:ONNX_Op<"Acos", let description = [{ "Calculates the arccosine (inverse of cosine) of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -66,8 +66,8 @@ def ONNXAcoshOp:ONNX_Op<"Acosh", let description = [{ "Calculates the hyperbolic arccosine of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -90,9 +90,9 @@ def ONNXAddOp:ONNX_Op<"Add", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -141,9 +141,9 @@ def ONNXAndOp:ONNX_Op<"And", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins TensorOf<[I1]>:$A, - TensorOf<[I1]>:$B); - let results = (outs TensorOf<[I1]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -192,7 +192,7 @@ def ONNXArgMaxOp:ONNX_Op<"ArgMax", "If keepdims equal 0, then the resulted tensor have the reduced dimension pruned. " "The type of the output tensor is integer." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, DefaultValuedAttr:$axis, DefaultValuedAttr:$keepdims); let results = (outs TensorOf<[I64]>:$reduced); @@ -218,7 +218,7 @@ def ONNXArgMinOp:ONNX_Op<"ArgMin", "If keepdims equal 0, then the resulted tensor have the reduced dimension pruned. " "The type of the output tensor is integer." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, DefaultValuedAttr:$axis, DefaultValuedAttr:$keepdims); let results = (outs TensorOf<[I64]>:$reduced); @@ -241,8 +241,8 @@ def ONNXAsinOp:ONNX_Op<"Asin", let description = [{ "Calculates the arcsine (inverse of sine) of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -262,8 +262,8 @@ def ONNXAsinhOp:ONNX_Op<"Asinh", let description = [{ "Calculates the hyperbolic arcsine of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -283,8 +283,8 @@ def ONNXAtanOp:ONNX_Op<"Atan", let description = [{ "Calculates the arctangent (inverse of tangent) of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -304,8 +304,8 @@ def ONNXAtanhOp:ONNX_Op<"Atanh", let description = [{ "Calculates the hyperbolic arctangent of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -353,14 +353,14 @@ def ONNXAveragePoolOp:ONNX_Op<"AveragePool", " The output of each pooling window is divided by the number of elements (exclude pad when attribute count_include_pad is zero)." " " }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$auto_pad, DefaultValuedAttr:$ceil_mode, DefaultValuedAttr:$count_include_pad, I64ArrayAttr:$kernel_shape, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -389,18 +389,18 @@ def ONNXBatchNormalizationOp:ONNX_Op<"BatchNormalization", "to flatten the input shape to (N x C*D1*D2 ..*Dn) before a BatchNormalization Op." "This operator has **optional** inputs/outputs. See [the doc](IR.md) for more details about the representation of optional arguments. An empty string may be used in the place of an actual argument's name to indicate a missing argument. Trailing optional arguments (those not followed by an argument that is present) may also be simply omitted." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$scale, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$mean, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$var, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$scale, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$mean, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$var, DefaultValuedAttr:$epsilon, DefaultValuedAttr:$momentum); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$out_mean, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType]>:$out_var, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType]>:$saved_mean, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType]>:$saved_var); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$out_mean, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType]>:$out_var, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType]>:$saved_mean, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType]>:$saved_var); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 5; @@ -431,10 +431,10 @@ def ONNXBitShiftOp:ONNX_Op<"BitShift", " not necessarily identical." "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>]>:$X, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>]>:$Y, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, AnyMemRef]>:$Y, StrAttr:$direction); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>]>:$Z); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, AnyMemRef]>:$Z); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -472,9 +472,9 @@ def ONNXCastOp:ONNX_Op<"Cast", "For example, a 64-bit float 3.1415926459 may be round to a 32-bit float 3.141592. Similarly, converting" "an integer 36 to Boolean may produce 1 because we truncate bits which can't be stored in the targeted type." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, TensorOf<[StringType]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, TensorOf<[StringType]>, AnyMemRef]>:$input, I64Attr:$to); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, TensorOf<[StringType]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, TensorOf<[StringType]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -504,8 +504,8 @@ def ONNXCeilOp:ONNX_Op<"Ceil", "(Tensor) where the ceil is, y = ceil(x), is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -527,10 +527,10 @@ def ONNXClipOp:ONNX_Op<"Clip", "specified by the inputs 'min' and 'max'. They default to" "numeric_limits::lowest() and numeric_limits::max(), respectively." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$min, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType]>:$max); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$min, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType]>:$max); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -553,10 +553,10 @@ def ONNXCompressOp:ONNX_Op<"Compress", " Compress behaves like numpy.compress: https://docs.scipy.org/doc/numpy/reference/generated/numpy.compress.html" " " }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, - TensorOf<[I1]>:$condition, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, + AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$condition, OptionalAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -576,9 +576,9 @@ def ONNXConcatOp:ONNX_Op<"Concat", let description = [{ "Concatenate a list of tensors into a single tensor. All input tensors must have the same shape, except for the dimension size of the axis to concatenate on." }]; - let arguments = (ins Variadic, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>>:$inputs, + let arguments = (ins Variadic, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>>:$inputs, I64Attr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$concat_result); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$concat_result); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -601,10 +601,10 @@ def ONNXConcatFromSequenceOp:ONNX_Op<"ConcatFromSequence", "By default 'new_axis' is 0, the behavior is similar to numpy.concatenate." "When 'new_axis' is 1, the behavior is similar to numpy.stack." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$input_sequence, + let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$input_sequence, I64Attr:$axis, DefaultValuedAttr:$new_axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$concat_result); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$concat_result); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -627,7 +627,7 @@ def ONNXConstantOp:ONNX_Op<"Constant", }]; let arguments = (ins OptionalAttr:$sparse_value, OptionalAttr:$value); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 0; @@ -667,9 +667,9 @@ def ONNXConstantOfShapeOp:ONNX_Op<"ConstantOfShape", let description = [{ "Generate a tensor with given value and shape." }]; - let arguments = (ins TensorOf<[I64]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$input, OptionalAttr:$value); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -691,16 +691,16 @@ def ONNXConvOp:ONNX_Op<"Conv", "The convolution operator consumes an input tensor and a filter, and" "computes the output." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$W, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$B, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$W, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$B, DefaultValuedAttr:$auto_pad, OptionalAttr:$dilations, DefaultValuedAttr:$group, OptionalAttr:$kernel_shape, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -721,17 +721,17 @@ def ONNXConvIntegerOp:ONNX_Op<"ConvInteger", "The integer convolution operator consumes an input tensor, its zero-point, a filter, and its zero-point," "and computes the output. The production MUST never overflow. The accumulation may overflow if and only if in 32 bits." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$x, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$w, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, NoneType]>:$x_zero_point, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, NoneType]>:$w_zero_point, + let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$x, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$w, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef, NoneType]>:$x_zero_point, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef, NoneType]>:$w_zero_point, DefaultValuedAttr:$auto_pad, OptionalAttr:$dilations, DefaultValuedAttr:$group, OptionalAttr:$kernel_shape, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs TensorOf<[I32]>:$y); + let results = (outs AnyTypeOf<[TensorOf<[I32]>, AnyMemRef]>:$y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 4; @@ -764,9 +764,9 @@ def ONNXConvTransposeOp:ONNX_Op<"ConvTranspose", "" " " }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$W, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$B, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$W, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$B, DefaultValuedAttr:$auto_pad, OptionalAttr:$dilations, DefaultValuedAttr:$group, @@ -775,7 +775,7 @@ def ONNXConvTransposeOp:ONNX_Op<"ConvTranspose", OptionalAttr:$output_shape, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -795,8 +795,8 @@ def ONNXCosOp:ONNX_Op<"Cos", let description = [{ "Calculates the cosine of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -816,8 +816,8 @@ def ONNXCoshOp:ONNX_Op<"Cosh", let description = [{ "Calculates the hyperbolic cosine of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -856,11 +856,11 @@ def ONNXCumSumOp:ONNX_Op<"CumSum", "```" " " }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$x, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$axis, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$x, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$axis, DefaultValuedAttr:$exclusive, DefaultValuedAttr:$reverse); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$y); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -906,10 +906,10 @@ def ONNXDepthToSpaceOp:ONNX_Op<"DepthToSpace", "y = np.reshape(tmp, [b, c // (blocksize ** 2), h * blocksize, w * blocksize])" "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, I64Attr:$blocksize, DefaultValuedAttr:$mode); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -932,9 +932,9 @@ def ONNXDequantizeLinearOp:ONNX_Op<"DequantizeLinear", "'x_zero_point' and 'x' must have same type. 'x' and 'y' must have same shape. In the case of dequantizing int32," "there's no zero point (zero point is supposed to be 0)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, TensorOf<[I32]>]>:$x, + let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, TensorOf<[I32]>, AnyMemRef]>:$x, TensorOf<[F32]>:$x_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, TensorOf<[I32]>, NoneType]>:$x_zero_point); + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, TensorOf<[I32]>, AnyMemRef, NoneType]>:$x_zero_point); let results = (outs TensorOf<[F32]>:$y); let extraClassDeclaration = [{ static int getNumberOfOperands() { @@ -959,8 +959,8 @@ def ONNXDetOp:ONNX_Op<"Det", "The output is a tensor of shape `[*]`, containing the determinants of all input submatrices." "e.g., When the input is 2-D, the output is a scalar(shape is empty: `[]`)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -982,9 +982,9 @@ def ONNXDivOp:ONNX_Op<"Div", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -1035,10 +1035,10 @@ def ONNXDropoutOp:ONNX_Op<"Dropout", "the training phase, so during testing nothing needs to be done." "This operator has **optional** inputs/outputs. See [the doc](IR.md) for more details about the representation of optional arguments. An empty string may be used in the place of an actual argument's name to indicate a missing argument. Trailing optional arguments (those not followed by an argument that is present) may also be simply omitted." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, DefaultValuedAttr:$ratio); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output, - AnyTypeOf<[TensorOf<[I1]>, NoneType]>:$mask); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output, + AnyTypeOf<[TensorOf<[I1]>, AnyMemRef, NoneType]>:$mask); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1079,10 +1079,10 @@ def ONNXDynamicQuantizeLinearOp:ONNX_Op<"DynamicQuantizeLinear", "* rounding to nearest ties to even." "```" }]; - let arguments = (ins TensorOf<[F32]>:$x); - let results = (outs TensorOf<[UI8]>:$y, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, AnyMemRef]>:$x); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, AnyMemRef]>:$y, TensorOf<[F32]>:$y_scale, - TensorOf<[UI8]>:$y_zero_point); + AnyTypeOf<[TensorOf<[UI8]>, AnyMemRef]>:$y_zero_point); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1105,9 +1105,9 @@ def ONNXEluOp:ONNX_Op<"Elu", "0`, `f(x) = x for x >= 0`., is applied to the tensor elementwise." "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$alpha); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1130,9 +1130,9 @@ def ONNXEqualOp:ONNX_Op<"Equal", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[I1]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs TensorOf<[I1]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[I1]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -1178,8 +1178,8 @@ def ONNXErfOp:ONNX_Op<"Erf", let description = [{ "Computes the error function of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1199,8 +1199,8 @@ def ONNXExpOp:ONNX_Op<"Exp", let description = [{ "Calculates the exponential of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value input", [{ auto elementType = input.getType().cast().getElementType(); @@ -1239,9 +1239,9 @@ def ONNXExpandOp:ONNX_Op<"Expand", "It is possible that the output.shape is not equal to shape, when some dimensions in shape is equal to 1," "or the shape.ndim < input.shape.ndim." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, TensorOf<[I64]>:$shape); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -1267,10 +1267,10 @@ def ONNXEyeLikeOp:ONNX_Op<"EyeLike", "The 'dtype' argument must be one of the data types specified in the 'DataType' enum field in the" "TensorProto message and be valid as an output type." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, AnyMemRef]>:$input, OptionalAttr:$dtype, DefaultValuedAttr:$k); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I1]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1292,9 +1292,9 @@ def ONNXFlattenOp:ONNX_Op<"Flatten", "(d_0, d_1, ... d_n) then the output will have shape" "(d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1316,8 +1316,8 @@ def ONNXFloorOp:ONNX_Op<"Floor", "(Tensor) where the floor is, y = floor(x), is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1409,12 +1409,12 @@ def ONNXGRUOp:ONNX_Op<"GRU", " - Ht = (1 - zt) (.) ht + zt (.) Ht-1" "This operator has **optional** inputs/outputs. See [the doc](IR.md) for more details about the representation of optional arguments. An empty string may be used in the place of an actual argument's name to indicate a missing argument. Trailing optional arguments (those not followed by an argument that is present) may also be simply omitted." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$W, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$R, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$B, - AnyTypeOf<[TensorOf<[I32]>, NoneType]>:$sequence_lens, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType]>:$initial_h, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$W, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$R, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$B, + AnyTypeOf<[TensorOf<[I32]>, AnyMemRef, NoneType]>:$sequence_lens, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType]>:$initial_h, OptionalAttr:$activation_alpha, OptionalAttr:$activation_beta, OptionalAttr:$activations, @@ -1422,8 +1422,8 @@ def ONNXGRUOp:ONNX_Op<"GRU", DefaultValuedAttr:$direction, OptionalAttr:$hidden_size, DefaultValuedAttr:$linear_before_reset); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType]>:$Y, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType]>:$Y_h); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType]>:$Y, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType]>:$Y_h); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 6; @@ -1499,10 +1499,10 @@ def ONNXGatherOp:ONNX_Op<"Gather", " ]" "```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$indices, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$indices, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -1576,10 +1576,10 @@ def ONNXGatherElementsOp:ONNX_Op<"GatherElements", " ]" "```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$indices, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$indices, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -1663,9 +1663,9 @@ def ONNXGatherNDOp:ONNX_Op<"GatherND", " output = [[[2,3]],[[4,5]]] # output_shape = [2, 1, 2] " "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, TensorOf<[I64]>:$indices); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -1698,14 +1698,14 @@ def ONNXGemmOp:ONNX_Op<"Gemm", "This operator supports **unidirectional broadcasting** (tensor C should be unidirectional broadcastable to tensor A * B); for more details please check [the doc](Broadcasting.md)." "This operator has **optional** inputs/outputs. See [the doc](IR.md) for more details about the representation of optional arguments. An empty string may be used in the place of an actual argument's name to indicate a missing argument. Trailing optional arguments (those not followed by an argument that is present) may also be simply omitted." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$A, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$B, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, NoneType]>:$C, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$B, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType]>:$C, DefaultValuedAttr:$alpha, DefaultValuedAttr:$beta, DefaultValuedAttr:$transA, DefaultValuedAttr:$transB); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, NoneType]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -1727,8 +1727,8 @@ def ONNXGlobalAveragePoolOp:ONNX_Op<"GlobalAveragePool", " the values in the same channel. This is equivalent to AveragePool with kernel size" " equal to the spatial dimension of input tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1750,9 +1750,9 @@ def ONNXGlobalLpPoolOp:ONNX_Op<"GlobalLpPool", " the values in the same channel. This is equivalent to LpPool with kernel size" " equal to the spatial dimension of input tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$p); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1774,8 +1774,8 @@ def ONNXGlobalMaxPoolOp:ONNX_Op<"GlobalMaxPool", " the values in the same channel. This is equivalent to MaxPool with kernel size" " equal to the spatial dimension of input tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1798,9 +1798,9 @@ def ONNXGreaterOp:ONNX_Op<"Greater", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs TensorOf<[I1]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -1848,10 +1848,10 @@ def ONNXHardSigmoidOp:ONNX_Op<"HardSigmoid", "(Tensor) where the HardSigmoid function, y = max(0, min(1, alpha * x + beta))," "is applied to the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$alpha, DefaultValuedAttr:$beta); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1884,9 +1884,9 @@ def ONNXHardmaxOp:ONNX_Op<"Hardmax", "will throw errors. The output tensor has the same shape" "and contains the hardmax values of the corresponding input." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1907,8 +1907,8 @@ def ONNXIdentityOp:ONNX_Op<"Identity", let description = [{ "Identity operator" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1928,10 +1928,10 @@ def ONNXIfOp:ONNX_Op<"If", let description = [{ "If conditional" }]; - let arguments = (ins TensorOf<[I1]>:$cond, + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$cond, AnyAttr:$else_branch, AnyAttr:$then_branch); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$outputs); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$outputs); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -1956,11 +1956,11 @@ def ONNXInstanceNormalizationOp:ONNX_Op<"InstanceNormalization", "where mean and variance are computed per instance per channel." "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$scale, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$scale, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B, DefaultValuedAttr:$epsilon); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -1980,10 +1980,10 @@ def ONNXIsInfOp:ONNX_Op<"IsInf", let description = [{ "Map infinity to true and other values to false." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$detect_negative, DefaultValuedAttr:$detect_positive); - let results = (outs TensorOf<[I1]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2003,8 +2003,8 @@ def ONNXIsNaNOp:ONNX_Op<"IsNaN", let description = [{ "Returns which elements of the input are NaN." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs TensorOf<[I1]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2033,12 +2033,12 @@ def ONNXLRNOp:ONNX_Op<"LRN", "" "Y[n, c, d1, ..., dk] = X[n, c, d1, ..., dk] / (bias + alpha / size * square_sum[n, c, d1, ..., dk] ) ^ beta" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$alpha, DefaultValuedAttr:$beta, DefaultValuedAttr:$bias, I64Attr:$size); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2138,14 +2138,14 @@ def ONNXLSTMOp:ONNX_Op<"LSTM", " - Ht = ot (.) h(Ct)" "This operator has **optional** inputs/outputs. See [the doc](IR.md) for more details about the representation of optional arguments. An empty string may be used in the place of an actual argument's name to indicate a missing argument. Trailing optional arguments (those not followed by an argument that is present) may also be simply omitted." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$W, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$R, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$B, - AnyTypeOf<[TensorOf<[I32]>, NoneType]>:$sequence_lens, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType]>:$initial_h, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType]>:$initial_c, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType]>:$P, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$W, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$R, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$B, + AnyTypeOf<[TensorOf<[I32]>, AnyMemRef, NoneType]>:$sequence_lens, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType]>:$initial_h, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType]>:$initial_c, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType]>:$P, OptionalAttr:$activation_alpha, OptionalAttr:$activation_beta, OptionalAttr:$activations, @@ -2153,9 +2153,9 @@ def ONNXLSTMOp:ONNX_Op<"LSTM", DefaultValuedAttr:$direction, OptionalAttr:$hidden_size, DefaultValuedAttr:$input_forget); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType, NoneType]>:$Y, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType, NoneType, NoneType]>:$Y_h, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType, NoneType, NoneType, NoneType]>:$Y_c); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType, NoneType]>:$Y, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType, NoneType, NoneType]>:$Y_h, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType, NoneType, NoneType, NoneType]>:$Y_c); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 8; @@ -2177,9 +2177,9 @@ def ONNXLeakyReluOp:ONNX_Op<"LeakyRelu", "output data (Tensor) where the function `f(x) = alpha * x for x < 0`," "`f(x) = x for x >= 0`, is applied to the data tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$alpha); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2202,9 +2202,9 @@ def ONNXLessOp:ONNX_Op<"Less", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs TensorOf<[I1]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -2250,8 +2250,8 @@ def ONNXLogOp:ONNX_Op<"Log", let description = [{ "Calculates the natural log of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2284,9 +2284,9 @@ def ONNXLogSoftmaxOp:ONNX_Op<"LogSoftmax", "will throw errors. The output tensor has the same shape" "and contains the logsoftmax values of the corresponding input." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2418,11 +2418,11 @@ def ONNXLoopOp:ONNX_Op<"Loop", "the scan_outputs from the previous layer, possibly going through several" "point-wise operators (e.g. dropout, residual connections, linear layer)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$M, - AnyTypeOf<[TensorOf<[I1]>, NoneType]>:$cond, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$v_initial, + let arguments = (ins AnyTypeOf<[TensorOf<[I64]>, AnyMemRef, NoneType]>:$M, + AnyTypeOf<[TensorOf<[I1]>, AnyMemRef, NoneType]>:$cond, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$v_initial, AnyAttr:$body); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$v_final_and_scan_outputs); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$v_final_and_scan_outputs); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -2442,10 +2442,10 @@ def ONNXLpNormalizationOp:ONNX_Op<"LpNormalization", let description = [{ "Given a matrix, apply Lp-normalization along the provided axis." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, DefaultValuedAttr:$axis, DefaultValuedAttr:$p); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2469,13 +2469,13 @@ def ONNXLpPoolOp:ONNX_Op<"LpPool", " of the input tensor according to the kernel size and downsampling the" " data into the output tensor Y for further processing." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$auto_pad, I64ArrayAttr:$kernel_shape, DefaultValuedAttr:$p, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2495,9 +2495,9 @@ def ONNXMatMulOp:ONNX_Op<"MatMul", let description = [{ "Matrix product that behaves like numpy.matmul: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$A, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$B); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -2518,11 +2518,11 @@ def ONNXMatMulIntegerOp:ONNX_Op<"MatMulInteger", "Matrix product that behaves like numpy.matmul: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html." "The production MUST never overflow. The accumulation may overflow if and only if in 32 bits." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$A, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$B, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, NoneType]>:$a_zero_point, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, NoneType]>:$b_zero_point); - let results = (outs TensorOf<[I32]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$B, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef, NoneType]>:$a_zero_point, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef, NoneType]>:$b_zero_point); + let results = (outs AnyTypeOf<[TensorOf<[I32]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 4; @@ -2544,8 +2544,8 @@ def ONNXMaxOp:ONNX_Op<"Max", "All inputs and outputs must have the same data type." "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>]>>:$data_0); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$max); + let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>>:$data_0); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$max); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -2593,7 +2593,7 @@ def ONNXMaxPoolOp:ONNX_Op<"MaxPool", " The output of each pooling window is maximum number of elements exclude pad." " " }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$auto_pad, DefaultValuedAttr:$ceil_mode, OptionalAttr:$dilations, @@ -2601,8 +2601,8 @@ def ONNXMaxPoolOp:ONNX_Op<"MaxPool", OptionalAttr:$pads, DefaultValuedAttr:$storage_order, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y, - AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$Indices); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y, + AnyTypeOf<[TensorOf<[I64]>, AnyMemRef, NoneType]>:$Indices); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2624,11 +2624,11 @@ def ONNXMaxRoiPoolOp:ONNX_Op<"MaxRoiPool", " apply max pooling across each RoI, to produce output 4-D tensor of shape" " (num_rois, channels, pooled_shape[0], pooled_shape[1])." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$rois, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$rois, I64ArrayAttr:$pooled_shape, DefaultValuedAttr:$spatial_scale); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -2665,13 +2665,13 @@ def ONNXMaxUnpoolOp:ONNX_Op<"MaxUnpool", " which define the exact unpooling op. The attributes typically have the same values as the corrsponding" " pooling op that the unpooling op is trying to invert." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - TensorOf<[I64]>:$I, - AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$output_shape, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$I, + AnyTypeOf<[TensorOf<[I64]>, AnyMemRef, NoneType]>:$output_shape, I64ArrayAttr:$kernel_shape, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -2693,8 +2693,8 @@ def ONNXMeanOp:ONNX_Op<"Mean", "All inputs and outputs must have the same data type." "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>]>>:$data_0); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$mean); + let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>>:$data_0); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$mean); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -2715,9 +2715,9 @@ def ONNXMeanVarianceNormalizationOp:ONNX_Op<"MeanVarianceNormalization", "A MeanVarianceNormalization Function: Perform mean variance normalization" " on the input tensor X using formula:
``` (X-EX)/sqrt(E(X-EX)^2) ```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$axes); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2739,8 +2739,8 @@ def ONNXMinOp:ONNX_Op<"Min", "All inputs and outputs must have the same data type." "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>]>>:$data_0); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$min); + let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>>:$data_0); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$min); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -2772,10 +2772,10 @@ def ONNXModOp:ONNX_Op<"Mod", "" " This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B, DefaultValuedAttr:$fmod); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$C); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$C); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -2797,9 +2797,9 @@ def ONNXMulOp:ONNX_Op<"Mul", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -2846,11 +2846,11 @@ def ONNXMultinomialOp:ONNX_Op<"Multinomial", "Generate a tensor of samples from a multinomial distribution according to the probabilities" "of each of the possible outcomes." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, DefaultValuedAttr:$dtype, DefaultValuedAttr:$sample_size, OptionalAttr:$seed); - let results = (outs AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2872,8 +2872,8 @@ def ONNXNegOp:ONNX_Op<"Neg", "(Tensor) where each element flipped sign, y = -x, is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[I32]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[I32]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[I32]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[I32]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2928,7 +2928,7 @@ def ONNXNonZeroOp:ONNX_Op<"NonZero", " NonZero behaves similar to numpy.nonzero:" " https://docs.scipy.org/doc/numpy/reference/generated/numpy.nonzero.html" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$X); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$X); let results = (outs TensorOf<[I64]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { @@ -2949,8 +2949,8 @@ def ONNXNotOp:ONNX_Op<"Not", let description = [{ "Returns the negation of the input tensor element-wise." }]; - let arguments = (ins TensorOf<[I1]>:$X); - let results = (outs TensorOf<[I1]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -2988,11 +2988,11 @@ def ONNXOneHotOp:ONNX_Op<"OneHot", " output[i, j, k, input[i, j, k]] = 1 for all i, j, k and 0 otherwise." "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$indices, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$depth, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$values, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$indices, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$depth, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$values, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -3015,9 +3015,9 @@ def ONNXOrOp:ONNX_Op<"Or", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins TensorOf<[I1]>:$A, - TensorOf<[I1]>:$B); - let results = (outs TensorOf<[I1]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -3066,9 +3066,9 @@ def ONNXPReluOp:ONNX_Op<"PRelu", "`f(x) = x for x >= 0`., is applied to the data tensor elementwise." "This operator supports **unidirectional broadcasting** (tensor slope should be unidirectional broadcastable to input tensor X); for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$slope); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$slope); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -3168,11 +3168,11 @@ def ONNXPadOp:ONNX_Op<"Pad", " ]" "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$pads, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$constant_value, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$constant_value, DefaultValuedAttr:$mode); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$output); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value data, Value pads, Value constant_value, StringAttr mode", [{ auto elementType = data.getType().cast().getElementType(); @@ -3210,9 +3210,9 @@ def ONNXPowOp:ONNX_Op<"Pow", "is applied to the data tensor elementwise." "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Z); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Z); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value X, Value Y", [{ auto lhsTy = X.getType().cast(); @@ -3262,22 +3262,22 @@ def ONNXQLinearConvOp:ONNX_Op<"QLinearConv", "It means they must be either scalars (per tensor) or 1-D tensors (per output channel)." "Each input or output and its related zero point must have same type." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$x, + let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$x, TensorOf<[F32]>:$x_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$x_zero_point, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$w, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$x_zero_point, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$w, TensorOf<[F32]>:$w_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$w_zero_point, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$w_zero_point, TensorOf<[F32]>:$y_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$y_zero_point, - AnyTypeOf<[TensorOf<[I32]>, NoneType]>:$B, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$y_zero_point, + AnyTypeOf<[TensorOf<[I32]>, AnyMemRef, NoneType]>:$B, DefaultValuedAttr:$auto_pad, OptionalAttr:$dilations, DefaultValuedAttr:$group, OptionalAttr:$kernel_shape, OptionalAttr:$pads, OptionalAttr:$strides); - let results = (outs AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$y); + let results = (outs AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 9; @@ -3304,15 +3304,15 @@ def ONNXQLinearMatMulOp:ONNX_Op<"QLinearMatMul", "and the number of elements of scale and zero point tensor of input 'b' should be equal to the number of columns of input 'b'." "Production must never overflow, and accumulation may overflow if and only if in 32 bits." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$a, + let arguments = (ins AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$a, TensorOf<[F32]>:$a_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$a_zero_point, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$b, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$a_zero_point, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$b, TensorOf<[F32]>:$b_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$b_zero_point, + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$b_zero_point, TensorOf<[F32]>:$y_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$y_zero_point); - let results = (outs AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>]>:$y); + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$y_zero_point); + let results = (outs AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef]>:$y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 8; @@ -3334,10 +3334,10 @@ def ONNXQuantizeLinearOp:ONNX_Op<"QuantizeLinear", "The quantization formula is y = saturate ((x / y_scale) + y_zero_point). For saturation, it saturates to [0, 255] if it's uint8, or [-128, 127] if it's int8." "For (x / y_scale), it's rounding to nearest ties to even. Refer to https://en.wikipedia.org/wiki/Rounding for details. 'y_zero_point' and 'y' must have same type." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[I32]>]>:$x, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[I32]>, AnyMemRef]>:$x, TensorOf<[F32]>:$y_scale, - AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, NoneType]>:$y_zero_point); - let results = (outs AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, NoneType]>:$y); + AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef, NoneType]>:$y_zero_point); + let results = (outs AnyTypeOf<[TensorOf<[I8]>, TensorOf<[UI8]>, AnyMemRef, NoneType]>:$y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -3417,20 +3417,20 @@ def ONNXRNNOp:ONNX_Op<"RNN", " - Ht = f(Xt*(Wi^T) + Ht-1*(Ri^T) + Wbi + Rbi)" "This operator has **optional** inputs/outputs. See [the doc](IR.md) for more details about the representation of optional arguments. An empty string may be used in the place of an actual argument's name to indicate a missing argument. Trailing optional arguments (those not followed by an argument that is present) may also be simply omitted." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$W, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$R, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType]>:$B, - AnyTypeOf<[TensorOf<[I32]>, NoneType]>:$sequence_lens, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType]>:$initial_h, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$W, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$R, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType]>:$B, + AnyTypeOf<[TensorOf<[I32]>, AnyMemRef, NoneType]>:$sequence_lens, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType]>:$initial_h, OptionalAttr:$activation_alpha, OptionalAttr:$activation_beta, DefaultValuedAttr:$activations, OptionalAttr:$clip, DefaultValuedAttr:$direction, OptionalAttr:$hidden_size); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType]>:$Y, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, NoneType, NoneType, NoneType, NoneType]>:$Y_h); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType]>:$Y, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef, NoneType, NoneType, NoneType, NoneType]>:$Y_h); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 6; @@ -3461,7 +3461,7 @@ def ONNXRandomNormalOp:ONNX_Op<"RandomNormal", DefaultValuedAttr:$scale, OptionalAttr:$seed, I64ArrayAttr:$shape); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 0; @@ -3487,12 +3487,12 @@ def ONNXRandomNormalLikeOp:ONNX_Op<"RandomNormalLike", "The 'dtype' argument must be one of the data types specified in the 'DataType' enum field in the" "TensorProto message, and be valid as an output type." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, OptionalAttr:$dtype, DefaultValuedAttr:$mean, DefaultValuedAttr:$scale, OptionalAttr:$seed); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3522,7 +3522,7 @@ def ONNXRandomUniformOp:ONNX_Op<"RandomUniform", DefaultValuedAttr:$low, OptionalAttr:$seed, I64ArrayAttr:$shape); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 0; @@ -3548,12 +3548,12 @@ def ONNXRandomUniformLikeOp:ONNX_Op<"RandomUniformLike", "The 'dtype' argument must be one of the data types specified in the 'DataType' enum field in the" "TensorProto message and be valid as an output type." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, OptionalAttr:$dtype, DefaultValuedAttr:$high, DefaultValuedAttr:$low, OptionalAttr:$seed); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3597,10 +3597,10 @@ def ONNXRangeOp:ONNX_Op<"Range", "Output: [10, 8, 6]" "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$start, - AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$limit, - AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$delta); - let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$start, + AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$limit, + AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$delta); + let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -3622,8 +3622,8 @@ def ONNXReciprocalOp:ONNX_Op<"Reciprocal", "(Tensor) where the reciprocal is, y = 1/x, is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3648,10 +3648,10 @@ def ONNXReduceL1Op:ONNX_Op<"ReduceL1", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3676,10 +3676,10 @@ def ONNXReduceL2Op:ONNX_Op<"ReduceL2", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3704,10 +3704,10 @@ def ONNXReduceLogSumOp:ONNX_Op<"ReduceLogSum", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3732,10 +3732,10 @@ def ONNXReduceLogSumExpOp:ONNX_Op<"ReduceLogSumExp", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3760,10 +3760,10 @@ def ONNXReduceMaxOp:ONNX_Op<"ReduceMax", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3788,10 +3788,10 @@ def ONNXReduceMeanOp:ONNX_Op<"ReduceMean", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3816,10 +3816,10 @@ def ONNXReduceMinOp:ONNX_Op<"ReduceMin", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3844,10 +3844,10 @@ def ONNXReduceProdOp:ONNX_Op<"ReduceProd", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3872,10 +3872,10 @@ def ONNXReduceSumOp:ONNX_Op<"ReduceSum", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value data, ArrayAttr axes, IntegerAttr keepdims", [{ auto elementType = data.getType().cast().getElementType(); @@ -3912,10 +3912,10 @@ def ONNXReduceSumSquareOp:ONNX_Op<"ReduceSumSquare", "The above behavior is similar to numpy, with the exception that numpy default keepdims to" "False instead of True." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$data, OptionalAttr:$axes, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$reduced); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$reduced); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value data, ArrayAttr axes, IntegerAttr keepdims", [{ auto elementType = data.getType().cast().getElementType(); @@ -3949,8 +3949,8 @@ def ONNXReluOp:ONNX_Op<"Relu", "(Tensor) where the rectified linear function, y = max(0, x), is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -3975,9 +3975,9 @@ def ONNXReshapeOp:ONNX_Op<"Reshape", "could also be 0, in which case the actual dimension value is unchanged (i.e. taken" "from the input tensor)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$shape); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$reshaped); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$reshaped); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -4002,8 +4002,8 @@ def ONNXResizeOp:ONNX_Op<"Resize", "Each dimension value of the output tensor is:" " output_dimension = floor(input_dimension * (roi_end - roi_start) * scale) if input \\"sizes\\" is not specified." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$roi, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$roi, TensorOf<[F32]>:$scales, AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$sizes, DefaultValuedAttr:$coordinate_transformation_mode, @@ -4012,7 +4012,7 @@ def ONNXResizeOp:ONNX_Op<"Resize", DefaultValuedAttr:$extrapolation_value, DefaultValuedAttr:$mode, DefaultValuedAttr:$nearest_mode); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 4; @@ -4064,11 +4064,11 @@ def ONNXReverseSequenceOp:ONNX_Op<"ReverseSequence", " [10.0, 9.0, 8.0, 11.0]," " [15.0, 14.0, 13.0, 12.0]]" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, TensorOf<[I64]>:$sequence_lens, DefaultValuedAttr:$batch_axis, DefaultValuedAttr:$time_axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -4098,15 +4098,15 @@ def ONNXRoiAlignOp:ONNX_Op<"RoiAlign", "the value of the sampled locations are computed directly" "through bilinear interpolation." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, - AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$rois, - TensorOf<[I64]>:$batch_indices, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$rois, + AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$batch_indices, DefaultValuedAttr:$mode, DefaultValuedAttr:$output_height, DefaultValuedAttr:$output_width, DefaultValuedAttr:$sampling_ratio, DefaultValuedAttr:$spatial_scale); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -4138,8 +4138,8 @@ def ONNXRoundOp:ONNX_Op<"Round", "round([-4.5]) = [-4.0]" "```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4279,14 +4279,14 @@ def ONNXScanOp:ONNX_Op<"Scan", " }" "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$initial_state_and_scan_inputs, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$initial_state_and_scan_inputs, AnyAttr:$body, I64Attr:$num_scan_inputs, OptionalAttr:$scan_input_axes, OptionalAttr:$scan_input_directions, OptionalAttr:$scan_output_axes, OptionalAttr:$scan_output_directions); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$final_state_and_scan_outputs); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$final_state_and_scan_outputs); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -4358,11 +4358,11 @@ def ONNXScatterOp:ONNX_Op<"Scatter", " output = [[1.0, 1.1, 3.0, 2.1, 5.0]]" "```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$indices, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$updates, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$indices, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$updates, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -4432,11 +4432,11 @@ def ONNXScatterElementsOp:ONNX_Op<"ScatterElements", " output = [[1.0, 1.1, 3.0, 2.1, 5.0]]" "```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$indices, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$updates, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$indices, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$updates, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -4511,10 +4511,10 @@ def ONNXScatterNDOp:ONNX_Op<"ScatterND", " [[8, 7, 6, 5], [4, 3, 2, 1], [1, 2, 3, 4], [5, 6, 7, 8]]]" "```" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, TensorOf<[I64]>:$indices, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$updates); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$updates); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -4537,10 +4537,10 @@ def ONNXSeluOp:ONNX_Op<"Selu", "`y = gamma * (alpha * e^x - alpha) for x <= 0`, `y = gamma * x for x > 0`," "is applied to the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$alpha, DefaultValuedAttr:$gamma); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4562,9 +4562,9 @@ def ONNXSequenceAtOp:ONNX_Op<"SequenceAt", "Accepted range for 'position' is in `[-n, n - 1]`, where `n` is the number of tensors in 'input_sequence'." "Negative value means counting positions from the back." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$input_sequence, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$position); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$tensor); + let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$input_sequence, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$position); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$tensor); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -4585,8 +4585,8 @@ def ONNXSequenceConstructOp:ONNX_Op<"SequenceConstruct", "Construct a tensor sequence containing 'inputs' tensors." "All tensors in 'inputs' must have the same data type." }]; - let arguments = (ins Variadic, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>>:$inputs); - let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$output_sequence); + let arguments = (ins Variadic, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>>:$inputs); + let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$output_sequence); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -4607,7 +4607,7 @@ def ONNXSequenceEmptyOp:ONNX_Op<"SequenceEmpty", "Construct an empty tensor sequence, with given data type." }]; let arguments = (ins OptionalAttr:$dtype); - let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 0; @@ -4630,9 +4630,9 @@ def ONNXSequenceEraseOp:ONNX_Op<"SequenceErase", "Negative value means counting positions from the back." "'position' is optional, by default it erases the last tensor from 'input_sequence'." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$input_sequence, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, NoneType]>:$position); - let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$output_sequence); + let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$input_sequence, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType]>:$position); + let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$output_sequence); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -4656,10 +4656,10 @@ def ONNXSequenceInsertOp:ONNX_Op<"SequenceInsert", "Negative value means counting positions from the back." "'position' is optional, by default it inserts 'tensor' to the back of 'input_sequence'." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$input_sequence, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$tensor, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, NoneType]>:$position); - let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$output_sequence); + let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$input_sequence, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$tensor, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType]>:$position); + let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$output_sequence); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -4679,8 +4679,8 @@ def ONNXSequenceLengthOp:ONNX_Op<"SequenceLength", let description = [{ "Produces a scalar(tensor of empty shape) containing the number of tensors in 'input_sequence'." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$input_sequence); - let results = (outs TensorOf<[I64]>:$length); + let arguments = (ins AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$input_sequence); + let results = (outs AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$length); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4700,8 +4700,8 @@ def ONNXShapeOp:ONNX_Op<"Shape", let description = [{ "Takes a tensor as input and outputs an 1D int64 tensor containing the shape of the input tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data); - let results = (outs TensorOf<[I64]>:$shape); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data); + let results = (outs AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$shape); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4724,10 +4724,10 @@ def ONNXShrinkOp:ONNX_Op<"Shrink", "bias. The formula of this operator is: If x < -lambd, y = x + bias;" "If x > lambd, y = x - bias; Otherwise, y = 0." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, DefaultValuedAttr:$bias, DefaultValuedAttr:$lambd); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4749,8 +4749,8 @@ def ONNXSigmoidOp:ONNX_Op<"Sigmoid", "(Tensor) where the sigmoid function, y = 1 / (1 + exp(-x)), is applied to the" "tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4771,8 +4771,8 @@ def ONNXSignOp:ONNX_Op<"Sign", "Calculate the sign of the given input tensor element-wise." "If input > 0, output 1. if input < 0, output -1. if input == 0, output 0." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4792,8 +4792,8 @@ def ONNXSinOp:ONNX_Op<"Sin", let description = [{ "Calculates the sine of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4813,8 +4813,8 @@ def ONNXSinhOp:ONNX_Op<"Sinh", let description = [{ "Calculates the hyperbolic sine of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4834,8 +4834,8 @@ def ONNXSizeOp:ONNX_Op<"Size", let description = [{ "Takes a tensor as input and outputs a int64 scalar that equals to the total number of elements of the input tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data); - let results = (outs TensorOf<[I64]>:$size); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data); + let results = (outs AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$size); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4888,12 +4888,12 @@ def ONNXSliceOp:ONNX_Op<"Slice", " [2, 3, 4]," " ]" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$starts, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>]>:$ends, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, NoneType]>:$axes, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, NoneType, NoneType]>:$steps); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$starts, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$ends, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType]>:$axes, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType, NoneType]>:$steps); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 5; @@ -4926,9 +4926,9 @@ def ONNXSoftmaxOp:ONNX_Op<"Softmax", "will throw errors. The output tensor has the same shape" "and contains the softmax values of the corresponding input." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input, DefaultValuedAttr:$axis); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4950,8 +4950,8 @@ def ONNXSoftplusOp:ONNX_Op<"Softplus", "(Tensor) where the softplus function, y = ln(exp(x) + 1), is applied to" "the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4971,8 +4971,8 @@ def ONNXSoftsignOp:ONNX_Op<"Softsign", let description = [{ "Calculates the softsign (x/(1+|x|)) of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -4994,9 +4994,9 @@ def ONNXSpaceToDepthOp:ONNX_Op<"SpaceToDepth", "this op outputs a copy of the input tensor where values from the height and width dimensions" "are moved to the depth dimension." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, I64Attr:$blocksize); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5018,10 +5018,10 @@ def ONNXSplitOp:ONNX_Op<"Split", "'axis'. Lengths of the parts can be specified using argument 'split'." "Otherwise, the tensor is split to equal sized parts." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, DefaultValuedAttr:$axis, OptionalAttr:$split); - let results = (outs Variadic, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>>:$outputs); + let results = (outs Variadic, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>>:$outputs); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5050,11 +5050,11 @@ def ONNXSplitToSequenceOp:ONNX_Op<"SplitToSequence", "specified in 'split'. In this scenario, the sum of entries in 'split' must be equal to the" "dimension size of input tensor on 'axis'." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, - AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, NoneType]>:$split, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, + AnyTypeOf<[TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef, NoneType]>:$split, DefaultValuedAttr:$axis, DefaultValuedAttr:$keepdims); - let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>]>:$output_sequence); + let results = (outs AnyTypeOf<[TensorOf<[TensorOf<[UI8]>]>, TensorOf<[TensorOf<[UI16]>]>, TensorOf<[TensorOf<[UI32]>]>, TensorOf<[TensorOf<[UI64]>]>, TensorOf<[TensorOf<[I8]>]>, TensorOf<[TensorOf<[I16]>]>, TensorOf<[TensorOf<[I32]>]>, TensorOf<[TensorOf<[I64]>]>, TensorOf<[TensorOf<[F16]>]>, TensorOf<[TensorOf<[F32]>]>, TensorOf<[TensorOf<[F64]>]>, TensorOf<[TensorOf<[StringType]>]>, TensorOf<[TensorOf<[I1]>]>, TensorOf<[TensorOf<[Complex]>]>, TensorOf<[TensorOf<[Complex]>]>, AnyMemRef]>:$output_sequence); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -5076,8 +5076,8 @@ def ONNXSqrtOp:ONNX_Op<"Sqrt", "(Tensor) where the square root is, y = x^0.5, is applied to" "the tensor elementwise. If x is negative, then it will return NaN." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5100,9 +5100,9 @@ def ONNXSqueezeOp:ONNX_Op<"Squeeze", "If `axes` is not provided, all the single dimensions will be removed from" "the shape. If an axis is selected with shape entry not equal to one, an error is raised." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, OptionalAttr:$axes); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$squeezed); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$squeezed); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5157,9 +5157,9 @@ def ONNXSubOp:ONNX_Op<"Sub", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$A, - AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$B); - let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -5207,8 +5207,8 @@ def ONNXSumOp:ONNX_Op<"Sum", "All inputs and outputs must have the same data type." "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>]>>:$data_0); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$sum); + let arguments = (ins Variadic, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>>:$data_0); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$sum); let extraClassDeclaration = [{ static int getNumberOfOperands() { return -1; @@ -5228,8 +5228,8 @@ def ONNXTanOp:ONNX_Op<"Tan", let description = [{ "Calculates the tangent of the given input tensor, element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5249,8 +5249,8 @@ def ONNXTanhOp:ONNX_Op<"Tanh", let description = [{ "Calculates the hyperbolic tangent of the given input tensor element-wise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$input); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$input); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5296,7 +5296,7 @@ def ONNXTfIdfVectorizerOp:ONNX_Op<"TfIdfVectorizer", "Only one of pool_strings and pool_int64s can be set. If pool_int64s is set, the input should be an integer tensor." "If pool_strings is set, the input must be a string tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I32]>, TensorOf<[I64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I32]>, TensorOf<[I64]>, AnyMemRef]>:$X, I64Attr:$max_gram_length, I64Attr:$max_skip_count, I64Attr:$min_gram_length, @@ -5306,7 +5306,7 @@ def ONNXTfIdfVectorizerOp:ONNX_Op<"TfIdfVectorizer", OptionalAttr:$pool_int64s, OptionalAttr:$pool_strings, OptionalAttr:$weights); - let results = (outs TensorOf<[F32]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F32]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5328,9 +5328,9 @@ def ONNXThresholdedReluOp:ONNX_Op<"ThresholdedRelu", "(Tensor) where the rectified linear function, y = x for x > alpha, y = 0 otherwise," "is applied to the tensor elementwise." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, DefaultValuedAttr:$alpha); - let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5352,9 +5352,9 @@ def ONNXTileOp:ONNX_Op<"Tile", "This is the same as function `tile` in Numpy, but no broadcast." "For example A = [[1, 2], [3, 4]], B = [1, 2], tile(A, B) = [[1, 2, 1, 2], [3, 4, 3, 4]]" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$input, - TensorOf<[I64]>:$repeats); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$input, + AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$repeats); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -5387,13 +5387,13 @@ def ONNXTopKOp:ONNX_Op<"TopK", "Given two equivalent values, this operator uses the indices along the axis as" " a tiebreaker. That is, the element with the lower index will appear first." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, TensorOf<[I64]>:$K, DefaultValuedAttr:$axis, DefaultValuedAttr:$largest, DefaultValuedAttr:$sorted); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$Values, - TensorOf<[I64]>:$Indices); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$Values, + AnyTypeOf<[TensorOf<[I64]>, AnyMemRef]>:$Indices); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -5415,9 +5415,9 @@ def ONNXTransposeOp:ONNX_Op<"Transpose", "perm=(1, 0, 2), given an input tensor of shape (1, 2, 3), the output shape" "will be (2, 1, 3)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, OptionalAttr:$perm); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$transposed); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$transposed); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5511,10 +5511,10 @@ def ONNXUniqueOp:ONNX_Op<"Unique", "" " output_counts = [2 1 1]" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$X, OptionalAttr:$axis, DefaultValuedAttr:$sorted); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$Y, + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$Y, AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$indices, AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$inverse_indices, AnyTypeOf<[TensorOf<[I64]>, NoneType]>:$counts); @@ -5548,9 +5548,9 @@ def ONNXUnsqueezeOp:ONNX_Op<"Unsqueeze", "The order of values in `axes` does not matter and can come in any order. " "" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$data, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$data, I64ArrayAttr:$axes); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$expanded); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$expanded); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5572,10 +5572,10 @@ def ONNXUpsampleOp:ONNX_Op<"Upsample", "Each dimension value of the output tensor is:" " output_dimension = floor(input_dimension * scale)." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$X, TensorOf<[F32]>:$scales, DefaultValuedAttr:$mode); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -5598,10 +5598,10 @@ def ONNXWhereOp:ONNX_Op<"Where", " Where behaves like numpy.where with three parameters:" " https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html" }]; - let arguments = (ins TensorOf<[I1]>:$condition, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$X, - AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$Y); - let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>]>:$output); + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$condition, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$X, + AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[UI8]>, TensorOf<[UI16]>, TensorOf<[UI32]>, TensorOf<[UI64]>, TensorOf<[I8]>, TensorOf<[I16]>, TensorOf<[I32]>, TensorOf<[I64]>, TensorOf<[F16]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, TensorOf<[I1]>, TensorOf<[Complex]>, TensorOf<[Complex]>, AnyMemRef]>:$output); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 3; @@ -5624,9 +5624,9 @@ def ONNXXorOp:ONNX_Op<"Xor", "" "This operator supports **multidirectional (i.e., Numpy-style) broadcasting**; for more details please check [the doc](Broadcasting.md)." }]; - let arguments = (ins TensorOf<[I1]>:$A, - TensorOf<[I1]>:$B); - let results = (outs TensorOf<[I1]>:$C); + let arguments = (ins AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$A, + AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$B); + let results = (outs AnyTypeOf<[TensorOf<[I1]>, AnyMemRef]>:$C); let builders = [ OpBuilder<"OpBuilder &builder, OperationState &state, Value A, Value B", [{ auto lhsTy = A.getType().cast(); @@ -5673,9 +5673,9 @@ def ONNXArrayFeatureExtractorOp:ONNX_Op<"ArrayFeatureExtractor", "Select elements of the input tensor based on the indices passed.
" " The indices are applied to the last axes of the tensor." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, TensorOf<[StringType]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, TensorOf<[StringType]>, AnyMemRef]>:$X, TensorOf<[I64]>:$Y); - let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, TensorOf<[StringType]>]>:$Z); + let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, TensorOf<[StringType]>, AnyMemRef]>:$Z); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 2; @@ -5695,9 +5695,9 @@ def ONNXBinarizerOp:ONNX_Op<"Binarizer", let description = [{ "Maps the values of the input tensor to either 0 or 1, element-wise, based on the outcome of a comparison against a threshold value." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, DefaultValuedAttr:$threshold); - let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5719,11 +5719,11 @@ def ONNXCastMapOp:ONNX_Op<"CastMap", " in ascending order based on this key.
The operator supports dense packing or sparse packing." " If using sparse packing, the key cannot exceed the max_map-1 value." }]; - let arguments = (ins AnyTypeOf<[TupleOf<[I64, StringType]>, TupleOf<[I64, F32]>]>:$X, + let arguments = (ins AnyTypeOf<[TupleOf<[I64, StringType]>, TupleOf<[I64, F32]>, AnyMemRef]>:$X, DefaultValuedAttr:$cast_to, DefaultValuedAttr:$map_form, DefaultValuedAttr:$max_map); - let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[F32]>, TensorOf<[I64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[F32]>, TensorOf<[I64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5750,12 +5750,12 @@ def ONNXCategoryMapperOp:ONNX_Op<"CategoryMapper", " If the string default value is set, it will convert integers to strings." " If the int default value is set, it will convert strings to integers." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, AnyMemRef]>:$X, OptionalAttr:$cats_int64s, OptionalAttr:$cats_strings, DefaultValuedAttr:$default_int64, DefaultValuedAttr:$default_string); - let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5786,10 +5786,10 @@ def ONNXDictVectorizerOp:ONNX_Op<"DictVectorizer", " then an input of ``{\"a\": 4, \"c\": 8}`` will produce an output of ``[4, 8, 0, 0]``." " " }]; - let arguments = (ins AnyTypeOf<[TupleOf<[StringType, I64]>, TupleOf<[I64, StringType]>, TupleOf<[I64, F32]>, TupleOf<[I64, F64]>, TupleOf<[StringType, F32]>, TupleOf<[StringType, F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TupleOf<[StringType, I64]>, TupleOf<[I64, StringType]>, TupleOf<[I64, F32]>, TupleOf<[I64, F64]>, TupleOf<[StringType, F32]>, TupleOf<[StringType, F64]>, AnyMemRef]>:$X, OptionalAttr:$int64_vocabulary, OptionalAttr:$string_vocabulary); - let results = (outs AnyTypeOf<[TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[StringType]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5812,7 +5812,7 @@ def ONNXFeatureVectorizerOp:ONNX_Op<"FeatureVectorizer", " Inputs are copied to the output maintaining the order of the input arguments.
" " All inputs must be integers or floats, while the output will be all floating point values." }]; - let arguments = (ins Variadic, TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>]>>:$X, + let arguments = (ins Variadic, TensorOf<[I64]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>>:$X, OptionalAttr:$inputdimensions); let results = (outs TensorOf<[F32]>:$Y); let extraClassDeclaration = [{ @@ -5841,12 +5841,12 @@ def ONNXImputerOp:ONNX_Op<"Imputer", " which one depends on whether floats or integers are being processed.
" " The imputed_value attribute length can be 1 element, or it can have one element per input feature.
In other words, if the input tensor has the shape [*,F], then the length of the attribute array may be 1 or F. If it is 1, then it is broadcast along the last dimension and applied to each feature." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$imputed_value_floats, OptionalAttr:$imputed_value_int64s, DefaultValuedAttr:$replaced_value_float, DefaultValuedAttr:$replaced_value_int64); - let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5882,7 +5882,7 @@ def ONNXLabelEncoderOp:ONNX_Op<"LabelEncoder", " For key look-up, bit-wise comparison is used so even a float NaN can be" " mapped to a value in 'values_*' attribute.
" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, TensorOf<[F32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, TensorOf<[F32]>, AnyMemRef]>:$X, DefaultValuedAttr:$default_float, DefaultValuedAttr:$default_int64, DefaultValuedAttr:$default_string, @@ -5892,7 +5892,7 @@ def ONNXLabelEncoderOp:ONNX_Op<"LabelEncoder", OptionalAttr:$values_floats, OptionalAttr:$values_int64s, OptionalAttr:$values_strings); - let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, TensorOf<[F32]>]>:$Y); + let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, TensorOf<[F32]>, AnyMemRef]>:$Y); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; @@ -5912,14 +5912,14 @@ def ONNXLinearClassifierOp:ONNX_Op<"LinearClassifier", let description = [{ "Linear classifier" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$classlabels_ints, OptionalAttr:$classlabels_strings, F32ArrayAttr:$coefficients, OptionalAttr:$intercepts, DefaultValuedAttr:$multi_class, DefaultValuedAttr:$post_transform); - let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>]>:$Y, + let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, AnyMemRef]>:$Y, TensorOf<[F32]>:$Z); let extraClassDeclaration = [{ static int getNumberOfOperands() { @@ -5945,7 +5945,7 @@ def ONNXLinearRegressorOp:ONNX_Op<"LinearRegressor", " The coefficients array is of length n, and the coefficients for each target are contiguous." " Intercepts are optional but if provided must match the number of targets." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$coefficients, OptionalAttr:$intercepts, DefaultValuedAttr:$post_transform, @@ -5979,7 +5979,7 @@ def ONNXNormalizerOp:ONNX_Op<"Normalizer", " For batches, that is, [N,C] tensors, normalization is done along the C axis. In other words, each row" " of the batch is normalized independently." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, DefaultValuedAttr:$norm); let results = (outs TensorOf<[F32]>:$Y); let extraClassDeclaration = [{ @@ -6008,7 +6008,7 @@ def ONNXOneHotEncoderOp:ONNX_Op<"OneHotEncoder", " If the input is a tensor of float, int32, or double, the data will be cast" " to integers and the cats_int64s category list will be used for the lookups." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, TensorOf<[I32]>, TensorOf<[F32]>, TensorOf<[F64]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, TensorOf<[I32]>, TensorOf<[F32]>, TensorOf<[F64]>, AnyMemRef]>:$X, OptionalAttr:$cats_int64s, OptionalAttr:$cats_strings, DefaultValuedAttr:$zeros); @@ -6032,7 +6032,7 @@ def ONNXSVMClassifierOp:ONNX_Op<"SVMClassifier", let description = [{ "Support Vector Machine classifier" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$classlabels_ints, OptionalAttr:$classlabels_strings, OptionalAttr:$coefficients, @@ -6044,7 +6044,7 @@ def ONNXSVMClassifierOp:ONNX_Op<"SVMClassifier", OptionalAttr:$rho, OptionalAttr:$support_vectors, OptionalAttr:$vectors_per_class); - let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>]>:$Y, + let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, AnyMemRef]>:$Y, TensorOf<[F32]>:$Z); let extraClassDeclaration = [{ static int getNumberOfOperands() { @@ -6065,7 +6065,7 @@ def ONNXSVMRegressorOp:ONNX_Op<"SVMRegressor", let description = [{ "Support Vector Machine regression prediction and one-class SVM anomaly detection." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$coefficients, OptionalAttr:$kernel_params, DefaultValuedAttr:$kernel_type, @@ -6094,7 +6094,7 @@ def ONNXScalerOp:ONNX_Op<"Scaler", let description = [{ "Rescale input data, for example to standardize features by removing the mean and scaling to unit variance." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$offset, OptionalAttr:$scale); let results = (outs TensorOf<[F32]>:$Y); @@ -6125,7 +6125,7 @@ def ONNXTreeEnsembleClassifierOp:ONNX_Op<"TreeEnsembleClassifier", " One and only one of classlabels_strings or classlabels_int64s" " will be defined. The class_ids are indices into this list." }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, OptionalAttr:$base_values, OptionalAttr:$class_ids, OptionalAttr:$class_nodeids, @@ -6143,7 +6143,7 @@ def ONNXTreeEnsembleClassifierOp:ONNX_Op<"TreeEnsembleClassifier", OptionalAttr:$nodes_truenodeids, OptionalAttr:$nodes_values, DefaultValuedAttr:$post_transform); - let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>]>:$Y, + let results = (outs AnyTypeOf<[TensorOf<[StringType]>, TensorOf<[I64]>, AnyMemRef]>:$Y, TensorOf<[F32]>:$Z); let extraClassDeclaration = [{ static int getNumberOfOperands() { @@ -6173,7 +6173,7 @@ def ONNXTreeEnsembleRegressorOp:ONNX_Op<"TreeEnsembleRegressor", " All trees must have their node ids start at 0 and increment by 1.
" " Mode enum is BRANCH_LEQ, BRANCH_LT, BRANCH_GTE, BRANCH_GT, BRANCH_EQ, BRANCH_NEQ, LEAF" }]; - let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>]>:$X, + let arguments = (ins AnyTypeOf<[TensorOf<[F32]>, TensorOf<[F64]>, TensorOf<[I64]>, TensorOf<[I32]>, AnyMemRef]>:$X, DefaultValuedAttr:$aggregate_function, OptionalAttr:$base_values, OptionalAttr:$n_targets, @@ -6217,7 +6217,7 @@ def ONNXZipMapOp:ONNX_Op<"ZipMap", let arguments = (ins TensorOf<[F32]>:$X, OptionalAttr:$classlabels_int64s, OptionalAttr:$classlabels_strings); - let results = (outs AnyTypeOf<[TensorOf<[TupleOf<[StringType, F32]>]>, TensorOf<[TupleOf<[I64, F32]>]>]>:$Z); + let results = (outs AnyTypeOf<[TensorOf<[TupleOf<[StringType, F32]>]>, TensorOf<[TupleOf<[I64, F32]>]>, AnyMemRef]>:$Z); let extraClassDeclaration = [{ static int getNumberOfOperands() { return 1; diff --git a/utils/gen_onnx_mlir.py b/utils/gen_onnx_mlir.py index 06c1e47..7b0e620 100644 --- a/utils/gen_onnx_mlir.py +++ b/utils/gen_onnx_mlir.py @@ -748,6 +748,9 @@ def parse_a_type_constraint(constraint): # However onnx keeps a consitently meaningful order # There is no redundancy as long as each onnx type is mapped uniquely # mlirTypes = sorted(list(set(mlirTypes))) + + # MemRef is always needed + mlirTypes.append("AnyMemRef") return mlirTypes def parse_type_constraints(schema):