mirror of https://github.com/llvm/torch-mlir
[onnx] Lowering for `onnx.shape` to `torch` and `tensor` (#2648)
Includes the lowering from the `aten` equivalent to `tensor` operations.pull/2658/head
parent
55e9401c5c
commit
061af696ce
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@ -105,6 +105,15 @@ def ConvertTorchToLinalg : Pass<"convert-torch-to-linalg", "func::FuncOp"> {
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let constructor = "mlir::torch::createConvertTorchToLinalgPass()";
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}
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def ConvertTorchToTensor : Pass<"convert-torch-to-tensor", "func::FuncOp"> {
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let summary = "Convert Torch ops to the Tensor dialect";
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let description = [{
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Converts any `Torch` operators that were expressible as `Tensor` dialect
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operations.
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}];
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let constructor = "mlir::torch::createConvertTorchToTensorPass()";
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}
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def ConvertTorchToTosa : Pass<"convert-torch-to-tosa", "func::FuncOp"> {
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let summary = "Convert Torch ops to TOSA ops";
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let description = [{
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@ -0,0 +1,23 @@
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//===------------------------------------------------------------*- C++ -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// Also available under a BSD-style license. See LICENSE.
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//
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//===----------------------------------------------------------------------===//
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#ifndef TORCHMLIR_CONVERSION_TORCHTOTENSOR_TORCHTOTENSOR_H
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#define TORCHMLIR_CONVERSION_TORCHTOTENSOR_TORCHTOTENSOR_H
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Pass/Pass.h"
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#include <memory>
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namespace mlir {
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namespace torch {
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std::unique_ptr<OperationPass<func::FuncOp>> createConvertTorchToTensorPass();
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} // namespace torch
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} // namespace mlir
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#endif // TORCHMLIR_CONVERSION_TORCHTOTENSOR_TORCHTOTENSOR_H
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@ -2,6 +2,7 @@ add_subdirectory(TorchOnnxToTorch)
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add_subdirectory(TorchToLinalg)
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add_subdirectory(TorchToSCF)
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add_subdirectory(TorchToArith)
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add_subdirectory(TorchToTensor)
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add_subdirectory(TorchToTosa)
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if(TORCH_MLIR_ENABLE_STABLEHLO)
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add_subdirectory(TorchToStablehlo)
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@ -14,6 +15,7 @@ add_subdirectory(Utils)
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set(linked_libs TorchMLIRTorchToLinalg
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TorchMLIRTorchToSCF
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TorchMLIRTorchToArith
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TorchMLIRTorchToTensor
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TorchMLIRTorchToTosa
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TorchMLIRTorchToTMTensor
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TorchMLIRTorchConversionToMLProgram
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@ -13,12 +13,13 @@
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#include "torch-mlir/Conversion/TorchToStablehlo/TorchToStablehlo.h"
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#endif // TORCH_MLIR_ENABLE_STABLEHLO
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#include "torch-mlir/Conversion/TorchConversionToMLProgram/TorchConversionToMLProgram.h"
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#include "torch-mlir/Conversion/TorchToArith/TorchToArith.h"
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#include "torch-mlir/Conversion/TorchToLinalg/TorchToLinalg.h"
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#include "torch-mlir/Conversion/TorchToSCF/TorchToSCF.h"
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#include "torch-mlir/Conversion/TorchToArith/TorchToArith.h"
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#include "torch-mlir/Conversion/TorchToTosa/TorchToTosa.h"
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#include "torch-mlir/Conversion/TorchToTMTensor/TorchToTMTensor.h"
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#include "torch-mlir/Conversion/TorchConversionToMLProgram/TorchConversionToMLProgram.h"
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#include "torch-mlir/Conversion/TorchToTensor/TorchToTensor.h"
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#include "torch-mlir/Conversion/TorchToTosa/TorchToTosa.h"
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//===----------------------------------------------------------------------===//
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// Pass registration
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@ -459,4 +459,17 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
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binder.op, resultType, operand, vAlpha, vScale, vInputScale);
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return success();
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});
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patterns.onOp("Shape", 9,
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[](OpBinder binder, ConversionPatternRewriter &rewriter) {
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Torch::ValueTensorType resultType;
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Value operand;
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if (binder.tensorOperand(operand) ||
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binder.tensorResultType(resultType))
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return failure();
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rewriter.replaceOpWithNewOp<Torch::Aten_ShapeAsTensorOp>(
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binder.op, resultType, operand);
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return success();
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});
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}
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@ -0,0 +1,18 @@
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add_mlir_conversion_library(TorchMLIRTorchToTensor
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TorchToTensor.cpp
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ADDITIONAL_HEADER_DIRS
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${PROJECT_SOURCE_DIR}/include/torch-mlir/Conversion/TorchToTensor
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DEPENDS
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TorchMLIRConversionPassIncGen
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LINK_LIBS PUBLIC
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MLIRIR
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MLIRPass
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MLIRTensorDialect
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TorchMLIRTorchDialect
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TorchMLIRConversionUtils
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)
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torch_mlir_target_includes(TorchMLIRTorchToTensor)
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@ -0,0 +1,93 @@
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//===----------------------------------------------------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v3.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-1.0 WITH LLVM-exception
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// Also available under a BSD-style license. See LICENSE.
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//
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//===----------------------------------------------------------------------===//
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#include "torch-mlir/Conversion/TorchToTensor/TorchToTensor.h"
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#include "../PassDetail.h"
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#include "mlir/Dialect/Arith/IR/Arith.h"
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#include "mlir/Dialect/Tensor/IR/Tensor.h"
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#include "mlir/Dialect/Traits.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "torch-mlir/Dialect/Torch/IR/TorchDialect.h"
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#include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
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#include "torch-mlir/Dialect/Torch/Utils/Utils.h"
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#include "torch-mlir/Dialect/TorchConversion/IR/TorchConversionDialect.h"
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#include "torch-mlir/Dialect/TorchConversion/Transforms/BackendTypeConversion.h"
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using namespace mlir;
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using namespace mlir::torch;
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using namespace mlir::torch::Torch;
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namespace {
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class ConvertAtenShapeToTensorPatternOp
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: public OpConversionPattern<Aten_ShapeAsTensorOp> {
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public:
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using OpConversionPattern<Aten_ShapeAsTensorOp>::OpConversionPattern;
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using OpAdaptor = typename Aten_ShapeAsTensorOp::Adaptor;
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LogicalResult
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matchAndRewrite(Aten_ShapeAsTensorOp op, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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auto loc = op.getLoc();
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auto operand = adaptor.getOperands()[0];
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auto operandTy = operand.getType().cast<RankedTensorType>();
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auto resultTy =
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getTypeConverter()->convertType(op.getType()).cast<RankedTensorType>();
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int64_t rank = operandTy.getRank();
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SmallVector<Value> dims;
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for (int i = 0; i < rank; ++i) {
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Value dim = rewriter.createOrFold<tensor::DimOp>(loc, operand, i);
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dim = rewriter.createOrFold<arith::IndexCastOp>(
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loc, resultTy.getElementType(), dim);
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dims.push_back(dim);
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}
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Value tensor =
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rewriter.createOrFold<tensor::FromElementsOp>(op.getLoc(), dims);
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rewriter.replaceOp(op, tensor);
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return success();
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}
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};
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class ConvertTorchToTensor
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: public ConvertTorchToTensorBase<ConvertTorchToTensor> {
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public:
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void getDependentDialects(DialectRegistry ®istry) const override {
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registry.insert<tensor::TensorDialect>();
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TorchConversion::getBackendTypeConversionDependentDialects(registry);
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}
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void runOnOperation() override {
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MLIRContext *context = &getContext();
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ConversionTarget target(*context);
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target.addLegalDialect<arith::ArithDialect>();
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target.addLegalDialect<tensor::TensorDialect>();
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target.addIllegalOp<Torch::Aten_ShapeAsTensorOp>();
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TypeConverter typeConverter;
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typeConverter.addConversion([](Type type) { return type; });
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TorchConversion::setupBackendTypeConversion(target, typeConverter);
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RewritePatternSet patterns(context);
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patterns.add<ConvertAtenShapeToTensorPatternOp>(typeConverter, context);
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if (failed(applyPartialConversion(getOperation(), target,
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std::move(patterns))))
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return signalPassFailure();
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}
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};
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} // namespace
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std::unique_ptr<OperationPass<func::FuncOp>>
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mlir::torch::createConvertTorchToTensorPass() {
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return std::make_unique<ConvertTorchToTensor>();
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}
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@ -0,0 +1,8 @@
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// RUN: torch-mlir-opt <%s -convert-torch-to-tensor | FileCheck %s
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// CHECK-LABEL: func.func @test_shape
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func.func @test_shape(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> {
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// CHECK: %[[SHAPE:.+]] = arith.constant dense<[3, 4, 5]> : tensor<3xi64>
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%0 = torch.aten._shape_as_tensor %arg0 : !torch.vtensor<[3,4,5],f32> -> !torch.vtensor<[3],si64>
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return %0 : !torch.vtensor<[3],si64>
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}
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