Files
clang-p2996/mlir/lib/Dialect/Tensor/Transforms/ConcatOpPatterns.cpp
MaheshRavishankar de6d48d05d [mlir][Tensor] Move concat operation decomposition as a method of the concat operation. (#116004)
Currently the implementation is within a pattern that cannot be used
without a pattern rewriter. Move the decomposition as a method of the
operation to make it usable outside of pattern rewrites.

Signed-off-by: MaheshRavishankar <mahesh.ravishankar@gmail.com>
2024-11-13 13:29:04 -08:00

53 lines
1.8 KiB
C++

//===- ConcatOpPatterns.cpp - Patterns related to tensor.concat lowering --===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Tensor/Transforms/Transforms.h"
#include "mlir/IR/PatternMatch.h"
using namespace mlir;
using namespace mlir::tensor;
namespace {
/// Decompose `tensor.concat` into `tensor.empty` and a chain of slice inserts.
///
/// %concat = tensor.concat dim(1) %0, %1 :
/// (tensor<2x3xf32>, tensor<2x4xf32>) -> tensor<2x7xf32>
///
/// Becomes
///
/// %empty = tensor.empty() : tensor<2x7xf32>
/// %insert0 = tensor.insert_slice %0 into %empty[0, 0][2, 3][1, 1]
/// %concat = tensor.insert_slice %1 into %insert0[0, 3][2, 4][1, 1]
struct DecomposeTensorConcatOp : public OpRewritePattern<ConcatOp> {
using OpRewritePattern<ConcatOp>::OpRewritePattern;
LogicalResult matchAndRewrite(ConcatOp concatOp,
PatternRewriter &rewriter) const override {
FailureOr<SmallVector<Value>> decomposed =
concatOp.decomposeOperation(rewriter);
if (failed(decomposed)) {
return rewriter.notifyMatchFailure(
concatOp, "failed to get the decomposed insert slices");
}
rewriter.replaceOp(concatOp, decomposed.value()[0]);
return success();
}
};
} // namespace
void mlir::tensor::populateDecomposeTensorConcatPatterns(
RewritePatternSet &patterns) {
patterns.add<DecomposeTensorConcatOp>(patterns.getContext());
}