mirror of https://github.com/llvm/torch-mlir
44 lines
1.4 KiB
C++
44 lines
1.4 KiB
C++
//===- ArrayToTensor.cpp -----------------------------------------*- C++-*-===//
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//
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// This file is licensed 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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//
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//===----------------------------------------------------------------------===//
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#include "PassDetail.h"
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#include "mlir/Dialect/StandardOps/IR/Ops.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/IR/BuiltinOps.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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#include "npcomp/Dialect/Numpy/IR/NumpyDialect.h"
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#include "npcomp/Dialect/Numpy/IR/NumpyOps.h"
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#include "npcomp/Dialect/Numpy/Transforms/Passes.h"
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using namespace mlir;
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using namespace mlir::NPCOMP;
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using namespace mlir::NPCOMP::Numpy;
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namespace {
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class ArrayToTensorPass : public NumpyArrayToTensorBase<ArrayToTensorPass> {
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void runOnOperation() override {
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MLIRContext *context = &getContext();
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auto func = getOperation();
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RewritePatternSet patterns(context);
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CopyToTensorOp::getCanonicalizationPatterns(patterns, context);
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StaticInfoCastOp::getCanonicalizationPatterns(patterns, context);
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(void)applyPatternsAndFoldGreedily(func, std::move(patterns));
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}
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};
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} // namespace
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std::unique_ptr<OperationPass<FuncOp>>
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mlir::NPCOMP::Numpy::createArrayToTensorPass() {
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return std::make_unique<ArrayToTensorPass>();
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}
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