1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
|
//===- Utils.cpp - Utilities to support the Tensor dialect ----------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements utilities for the Tensor dialect.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Tensor/Utils/Utils.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
using namespace mlir;
using namespace mlir::tensor;
PadOp mlir::tensor::createPadHighOp(RankedTensorType type, Value source,
Value pad, bool nofold, Location loc,
OpBuilder &b) {
auto zero = b.createOrFold<arith::ConstantIndexOp>(loc, 0);
SmallVector<OpFoldResult> low(type.getRank(), zero);
SmallVector<OpFoldResult> high(type.getRank(), zero);
for (const auto &en : enumerate(type.getShape())) {
// Pad only the static dimensions of the result tensor type.
if (ShapedType::isDynamic(en.value()))
continue;
// Compute the padding width.
AffineExpr d0;
bindDims(b.getContext(), d0);
auto dimOp = b.createOrFold<tensor::DimOp>(loc, source, en.index());
high[en.index()] =
makeComposedAffineApply(b, loc, en.value() - d0, {dimOp}).getResult();
}
return b.create<PadOp>(loc, type, source, low, high, pad, nofold);
}
SmallVector<Value> mlir::tensor::createDynamicDimValues(OpBuilder &b,
Location loc,
Value rankedTensor) {
auto tensorTy = rankedTensor.getType().cast<RankedTensorType>();
SmallVector<Value> dynamicDims;
for (const auto &en : llvm::enumerate(tensorTy.getShape())) {
if (en.value() == ShapedType::kDynamic)
dynamicDims.push_back(
b.create<tensor::DimOp>(loc, rankedTensor, en.index()));
}
return dynamicDims;
}
SmallVector<OpFoldResult>
mlir::tensor::createDimValues(OpBuilder &b, Location loc, Value rankedTensor) {
auto tensorTy = rankedTensor.getType().cast<RankedTensorType>();
SmallVector<OpFoldResult> dims;
for (const auto &en : llvm::enumerate(tensorTy.getShape())) {
if (ShapedType::isDynamic(en.value())) {
dims.push_back(
b.createOrFold<tensor::DimOp>(loc, rankedTensor, en.index()));
} else {
dims.push_back(b.getIndexAttr(en.value()));
}
}
return dims;
}
|
