65 lines
1.9 KiB
TableGen
65 lines
1.9 KiB
TableGen
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//===- ONNXOps.td -- ONNX operation definitions ---------*- tablegen -*----===//
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//
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// Copyright 2019 The IBM Research Authors
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//
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// =============================================================================
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//
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// Defines MLIR ONNX operations.
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//
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//===----------------------------------------------------------------------===//
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#ifdef ONNX_OPS
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#else
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#define ONNX_OPS
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#ifdef OP_BASE
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#else
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include "mlir/IR/OpBase.td"
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#endif // OP_BASE
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def ONNX_Dialect : Dialect {
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let name = "onnx";
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let cppNamespace = "";
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}
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// Base class for ONNX dialect operations. This operation inherits from the base
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// `Op` class in OpBase.td, and provides:
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// * The parent dialect of the operation.
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// * The mnemonic for the operation, or the name without the dialect prefix.
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// * A list of traits for the operation.
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class ONNX_Op<string mnemonic, list<OpTrait> traits = []> :
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Op<ONNX_Dialect, mnemonic, traits>;
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//===----------------------------------------------------------------------===//
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// ONNX Operations
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//===----------------------------------------------------------------------===//
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// We define an ONNX operation for adding two tensors elementwise.
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def ONNXAddOp: ONNX_Op<"add", [NoSideEffect]> {
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let summary = "ONNX add operation";
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let description = [{
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The "onnx.add" adds two tensors element-wise.
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}];
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// TODO: AnyTensor might be too wide for ONNX and may need to be constrained
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// to fewer valid types.
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// In the ONNX spec:
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// T : tensor(uint32), tensor(uint64),
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// tensor(int32), tensor(int64),
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// tensor(float16), tensor(float), tensor(double)
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//
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let arguments = (ins AnyTensor:$lhs_in, AnyTensor:$rhs_in);
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let results = (outs AnyTensor);
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// Build an ONNX Add operation using two input operands.
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let builders = [
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OpBuilder<"Builder *b, OperationState &result, Value *lhs, Value *rhs", [{
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buildONNXAddOp(b, result, lhs, rhs);
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}]
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>];
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}
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#endif // ONNX_OPS
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