Fix Gemm translation to ONNX dialect.
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@ -79,17 +79,17 @@ def ONNXEntryPointOp: ONNX_Op<"EntryPoint"> {
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}
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def ONNXFullGemmOp: ONNX_Op<"FullGemm",
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def ONNXGemmNoBiasOp: ONNX_Op<"GemmNoBias",
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[NoSideEffect, DeclareOpInterfaceMethods<ShapeInferenceOpInterface>]> {
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let summary = "ONNX general matrix multiply operation";
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let summary = "ONNX general matrix multiply operation without bias.";
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let description = [{
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The "onnx.gemm" generic matrix multiplication with bias.
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The "onnx.Gemm" generic matrix multiplication without bias.
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}];
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let arguments = (ins AnyTensor:$lhs_in, AnyTensor:$rhs_in, AnyTensor:$bias_in);
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let results = (outs AnyTensor);
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let arguments = (ins AnyTypeOf<[AnyMemRef, AnyTensor]>:$lhs_in, AnyTypeOf<[AnyMemRef, AnyTensor]>:$rhs_in);
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let results = (outs AnyTypeOf<[AnyMemRef, AnyTensor]>);
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}
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def ONNXConv1Op:ONNX_Op<"Conv1",
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@ -349,7 +349,7 @@ void ONNXGemmOp::inferShapes() {
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// FullGemm
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void ONNXFullGemmOp::inferShapes() {
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void ONNXGemmNoBiasOp::inferShapes() {
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// Cannot infer shape if no shape exists.
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if (!getOperand(0).getType().isa<RankedTensorType>() ||
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!getOperand(1).getType().isa<RankedTensorType>())
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@ -32,7 +32,7 @@ def HasOneUse : Constraint<CPred<"$0.hasOneUse()">>;
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// onnx.add(onnx.matmul(%X, %Y), %Z) = onnx.FullGemm(%X, %Y, %Z)
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def MulAddToGemmOptPattern : Pat<(ONNXAddOp (ONNXMatMulOp:$res $m1, $m2), $m3),
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(ONNXFullGemmOp $m1, $m2, $m3),
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(ONNXGemmOp $m1, $m2, $m3),
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[(HasOneUse $res)]>;
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// ONNX_Op (onnx.Identity (%X)) = ONNX_Op (%X)
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@ -2,7 +2,7 @@
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func @test_matmul_add_simplification(%a0: tensor<10x10xf32>, %a1: tensor<10x10xf32>, %a2: tensor<10x10xf32>) -> tensor<10x10xf32> {
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// CHECK-LABEL: test_matmul_add_simplification
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// CHECK: %{{[0-9]+}} = "onnx.FullGemm"(%{{.*}}, %{{.*}}, %{{.*}}) : (tensor<10x10xf32>, tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
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// CHECK: %{{[0-9]+}} = "onnx.Gemm"(%{{.*}}, %{{.*}}, %{{.*}}) : (tensor<10x10xf32>, tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
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%0 = "onnx.MatMul"(%a0, %a1) : (tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
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%1 = "onnx.Add"(%0, %a2) : (tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
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"std.return"(%1) : (tensor<10x10xf32>) -> ()
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