mirror of https://github.com/llvm/torch-mlir
71 lines
2.3 KiB
C++
71 lines
2.3 KiB
C++
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//===----------------------------------------------------------------------===//
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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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#include "PassDetail.h"
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#include "mlir/Dialect/StandardOps/IR/Ops.h"
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#include "mlir/IR/BlockAndValueMapping.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/Parser.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "mlir/Transforms/InliningUtils.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/Transforms/Passes.h"
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#include "torch-mlir/Dialect/Torch/Utils/Utils.h"
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#include "llvm/ADT/StringExtras.h"
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#include "llvm/ADT/StringSet.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 DropShapeCalculateOp : public OpConversionPattern<ShapeCalculateOp> {
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public:
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(ShapeCalculateOp op, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Block *block = &op.body().front();
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Operation *terminator = block->getTerminator();
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ValueRange results = terminator->getOperands();
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rewriter.mergeBlockBefore(block, op);
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rewriter.replaceOp(op, results);
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rewriter.eraseOp(terminator);
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return success();
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}
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};
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} // namespace
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namespace {
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class DropShapeCalculationsPass
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: public DropShapeCalculationsBase<DropShapeCalculationsPass> {
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void runOnOperation() override {
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MLIRContext *context = &getContext();
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RewritePatternSet patterns(context);
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patterns.insert<DropShapeCalculateOp>(context);
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ConversionTarget target(*context);
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target.addIllegalOp<ShapeCalculateOp>();
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target.addLegalOp<FuncOp>();
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if (failed(applyPartialConversion(getOperation(), target,
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std::move(patterns)))) {
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signalPassFailure();
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}
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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::torch::Torch::createDropShapeCalculationsPass() {
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return std::make_unique<DropShapeCalculationsPass>();
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}
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