a54f4eae0e
Precursor: https://reviews.llvm.org/D110200 Removed redundant ops from the standard dialect that were moved to the `arith` or `math` dialects. Renamed all instances of operations in the codebase and in tests. Reviewed By: rriddle, jpienaar Differential Revision: https://reviews.llvm.org/D110797
132 lines
4.7 KiB
C++
132 lines
4.7 KiB
C++
//===- Bufferize.cpp - Bufferization for std ops --------------------------===//
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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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//
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//===----------------------------------------------------------------------===//
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//
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// This file implements bufferization of tensor-valued arith.constant ops.
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//
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//===----------------------------------------------------------------------===//
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#include "PassDetail.h"
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#include "mlir/Dialect/MemRef/IR/MemRef.h"
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#include "mlir/Dialect/StandardOps/IR/Ops.h"
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#include "mlir/Dialect/StandardOps/Transforms/Passes.h"
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#include "mlir/IR/BlockAndValueMapping.h"
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#include "mlir/Transforms/BufferUtils.h"
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#include "mlir/Transforms/Bufferize.h"
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#include "mlir/Transforms/DialectConversion.h"
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using namespace mlir;
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memref::GlobalOp GlobalCreator::getGlobalFor(arith::ConstantOp constantOp) {
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auto type = constantOp.getType().cast<RankedTensorType>();
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BufferizeTypeConverter typeConverter;
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// If we already have a global for this constant value, no need to do
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// anything else.
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auto it = globals.find(constantOp.value());
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if (it != globals.end())
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return cast<memref::GlobalOp>(it->second);
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// Create a builder without an insertion point. We will insert using the
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// symbol table to guarantee unique names.
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OpBuilder globalBuilder(moduleOp.getContext());
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SymbolTable symbolTable(moduleOp);
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// Create a pretty name.
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SmallString<64> buf;
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llvm::raw_svector_ostream os(buf);
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interleave(type.getShape(), os, "x");
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os << "x" << type.getElementType();
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// Add an optional alignment to the global memref.
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IntegerAttr memrefAlignment =
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alignment > 0 ? IntegerAttr::get(globalBuilder.getI64Type(), alignment)
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: IntegerAttr();
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auto global = globalBuilder.create<memref::GlobalOp>(
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constantOp.getLoc(), (Twine("__constant_") + os.str()).str(),
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/*sym_visibility=*/globalBuilder.getStringAttr("private"),
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/*type=*/typeConverter.convertType(type).cast<MemRefType>(),
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/*initial_value=*/constantOp.value().cast<ElementsAttr>(),
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/*constant=*/true,
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/*alignment=*/memrefAlignment);
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symbolTable.insert(global);
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// The symbol table inserts at the end of the module, but globals are a bit
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// nicer if they are at the beginning.
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global->moveBefore(&moduleOp.front());
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globals[constantOp.value()] = global;
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return global;
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}
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namespace {
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class BufferizeTensorConstantOp
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: public OpConversionPattern<arith::ConstantOp> {
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public:
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BufferizeTensorConstantOp(GlobalCreator &globals,
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TypeConverter &typeConverter, MLIRContext *context)
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: OpConversionPattern<arith::ConstantOp>(typeConverter, context,
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/*benefit=*/1),
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globals(globals) {}
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LogicalResult
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matchAndRewrite(arith::ConstantOp op, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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auto type = op.getType().dyn_cast<RankedTensorType>();
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if (!type)
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return failure();
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auto globalMemref = globals.getGlobalFor(op);
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rewriter.replaceOpWithNewOp<memref::GetGlobalOp>(op, globalMemref.type(),
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globalMemref.getName());
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return success();
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}
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GlobalCreator &globals;
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};
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} // namespace
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void mlir::populateTensorConstantBufferizePatterns(
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GlobalCreator &globalCreator, BufferizeTypeConverter &typeConverter,
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RewritePatternSet &patterns) {
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patterns.add<BufferizeTensorConstantOp>(globalCreator, typeConverter,
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patterns.getContext());
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}
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namespace {
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class TensorConstantBufferizePass
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: public TensorConstantBufferizeBase<TensorConstantBufferizePass> {
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public:
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explicit TensorConstantBufferizePass(unsigned alignment) {
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if (alignment)
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this->alignment = alignment;
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}
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void runOnOperation() override {
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auto module = getOperation();
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GlobalCreator globals(module, alignment);
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auto *context = &getContext();
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BufferizeTypeConverter typeConverter;
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RewritePatternSet patterns(context);
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ConversionTarget target(*context);
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target.addLegalDialect<memref::MemRefDialect>();
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populateTensorConstantBufferizePatterns(globals, typeConverter, patterns);
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target.addDynamicallyLegalOp<arith::ConstantOp>([&](arith::ConstantOp op) {
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return typeConverter.isLegal(op.getType());
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});
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if (failed(applyPartialConversion(module, target, std::move(patterns))))
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signalPassFailure();
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}
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};
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} // namespace
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std::unique_ptr<Pass>
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mlir::createTensorConstantBufferizePass(unsigned alignment) {
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return std::make_unique<TensorConstantBufferizePass>(alignment);
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}
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