This PR *restricts* `GeneralizeOuterUnitDimsPackOpPattern` to follow its
intended purpose (as per the documentation), which is to:
> require all outer dimensions of tensor.pack to be 1.
There was one in-tree test that violated this assumption (and happened
to work) – see `@simple_KCRS_to_KRSCsr` in
"generalize-tensor-pack.mlir". That test has been updated to satisfy the
new requirements of the pattern.
By enforcing the pattern to follow its intended design (i.e., making it
stricter), the calculation of shapes and sizes for various Ops that the
pattern generates (PadOp, ExtractSliceOp, EmptyOp, TensorOp, and
InsertSliceOp) becomes much simpler and easier to document. This also
helped *generalize* the pattern to support cases like the one below:
```mlir
func.func @simple_pad_and_pack_dynamic_tile_cst(
%src: tensor<5x1xf32>,
%dest: tensor<1x1x?x2xf32>,
%pad: f32) -> tensor<1x1x?x2xf32> {
%tile_dim_0 = arith.constant 8 : index
%0 = tensor.pack %src
padding_value(%pad : f32)
inner_dims_pos = [0, 1]
inner_tiles = [%tile_dim_0, 2]
into %dest : tensor<5x1xf32> -> tensor<1x1x?x2xf32>
return %0 : tensor<1x1x?x2xf32>
}
```
Note that the inner tile slice is dynamic but compile-time constant.
`getPackOpSourceOrPaddedSource`, which is used to generate PadOp,
detects this and generates a PadOp with static shapes. This is a good
optimization, but it means that all shapes/sizes for Ops generated by
`GeneralizeOuterUnitDimsPackOpPattern` also need to be updated to be
constant/static. By restricting the pattern and simplifying the
size/shape calculation, supporting the case above becomes much easier.
Notable implementation changes:
* PadOp processes the original source (no change in dimensions/rank).
ExtractSliceOp extracts the tile to pack and may reduce the rank. All
following ops work on the tile extracted by ExtractSliceOp (possibly
rank-reduced).
* All shape/size calculations assume that trailing dimensions match
inner_tiles from tensor.pack. All leading dimensions (i.e., outer
dimensions) are assumed to be 1.
* Dynamic sizes for ops like ExtractSliceOp are taken from inner_tiles
rather than computed as, for example, tensor.dim %dest, 2. It’s the
responsibility of the "producers" of tensor.pack to ensure that
dimensions in %dest match the specified tile sizes.
325 lines
11 KiB
C++
325 lines
11 KiB
C++
//===- StaticValueUtils.cpp - Utilities for dealing with static values ----===//
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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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#include "mlir/Dialect/Utils/StaticValueUtils.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/Support/LLVM.h"
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#include "llvm/ADT/APSInt.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/Support/MathExtras.h"
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namespace mlir {
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bool isZeroIndex(OpFoldResult v) {
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if (!v)
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return false;
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std::optional<int64_t> constint = getConstantIntValue(v);
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if (!constint)
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return false;
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return *constint == 0;
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}
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std::tuple<SmallVector<OpFoldResult>, SmallVector<OpFoldResult>,
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SmallVector<OpFoldResult>>
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getOffsetsSizesAndStrides(ArrayRef<Range> ranges) {
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SmallVector<OpFoldResult> offsets, sizes, strides;
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offsets.reserve(ranges.size());
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sizes.reserve(ranges.size());
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strides.reserve(ranges.size());
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for (const auto &[offset, size, stride] : ranges) {
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offsets.push_back(offset);
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sizes.push_back(size);
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strides.push_back(stride);
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}
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return std::make_tuple(offsets, sizes, strides);
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}
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/// Helper function to dispatch an OpFoldResult into `staticVec` if:
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/// a) it is an IntegerAttr
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/// In other cases, the OpFoldResult is dispached to the `dynamicVec`.
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/// In such dynamic cases, a copy of the `sentinel` value is also pushed to
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/// `staticVec`. This is useful to extract mixed static and dynamic entries that
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/// come from an AttrSizedOperandSegments trait.
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void dispatchIndexOpFoldResult(OpFoldResult ofr,
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SmallVectorImpl<Value> &dynamicVec,
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SmallVectorImpl<int64_t> &staticVec) {
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auto v = llvm::dyn_cast_if_present<Value>(ofr);
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if (!v) {
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APInt apInt = cast<IntegerAttr>(ofr.get<Attribute>()).getValue();
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staticVec.push_back(apInt.getSExtValue());
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return;
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}
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dynamicVec.push_back(v);
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staticVec.push_back(ShapedType::kDynamic);
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}
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std::pair<int64_t, OpFoldResult>
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getSimplifiedOfrAndStaticSizePair(OpFoldResult tileSizeOfr, Builder &b) {
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int64_t tileSizeForShape =
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getConstantIntValue(tileSizeOfr).value_or(ShapedType::kDynamic);
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OpFoldResult tileSizeOfrSimplified =
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(tileSizeForShape != ShapedType::kDynamic)
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? b.getIndexAttr(tileSizeForShape)
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: tileSizeOfr;
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return std::pair<int64_t, OpFoldResult>(tileSizeForShape,
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tileSizeOfrSimplified);
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}
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void dispatchIndexOpFoldResults(ArrayRef<OpFoldResult> ofrs,
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SmallVectorImpl<Value> &dynamicVec,
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SmallVectorImpl<int64_t> &staticVec) {
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for (OpFoldResult ofr : ofrs)
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dispatchIndexOpFoldResult(ofr, dynamicVec, staticVec);
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}
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/// Given a value, try to extract a constant Attribute. If this fails, return
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/// the original value.
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OpFoldResult getAsOpFoldResult(Value val) {
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if (!val)
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return OpFoldResult();
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Attribute attr;
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if (matchPattern(val, m_Constant(&attr)))
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return attr;
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return val;
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}
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/// Given an array of values, try to extract a constant Attribute from each
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/// value. If this fails, return the original value.
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SmallVector<OpFoldResult> getAsOpFoldResult(ValueRange values) {
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return llvm::to_vector(
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llvm::map_range(values, [](Value v) { return getAsOpFoldResult(v); }));
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}
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/// Convert `arrayAttr` to a vector of OpFoldResult.
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SmallVector<OpFoldResult> getAsOpFoldResult(ArrayAttr arrayAttr) {
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SmallVector<OpFoldResult> res;
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res.reserve(arrayAttr.size());
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for (Attribute a : arrayAttr)
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res.push_back(a);
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return res;
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}
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OpFoldResult getAsIndexOpFoldResult(MLIRContext *ctx, int64_t val) {
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return IntegerAttr::get(IndexType::get(ctx), val);
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}
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SmallVector<OpFoldResult> getAsIndexOpFoldResult(MLIRContext *ctx,
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ArrayRef<int64_t> values) {
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return llvm::to_vector(llvm::map_range(
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values, [ctx](int64_t v) { return getAsIndexOpFoldResult(ctx, v); }));
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}
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/// If ofr is a constant integer or an IntegerAttr, return the integer.
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std::optional<int64_t> getConstantIntValue(OpFoldResult ofr) {
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// Case 1: Check for Constant integer.
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if (auto val = llvm::dyn_cast_if_present<Value>(ofr)) {
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APSInt intVal;
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if (matchPattern(val, m_ConstantInt(&intVal)))
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return intVal.getSExtValue();
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return std::nullopt;
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}
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// Case 2: Check for IntegerAttr.
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Attribute attr = llvm::dyn_cast_if_present<Attribute>(ofr);
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if (auto intAttr = dyn_cast_or_null<IntegerAttr>(attr))
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return intAttr.getValue().getSExtValue();
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return std::nullopt;
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}
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std::optional<SmallVector<int64_t>>
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getConstantIntValues(ArrayRef<OpFoldResult> ofrs) {
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bool failed = false;
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SmallVector<int64_t> res = llvm::map_to_vector(ofrs, [&](OpFoldResult ofr) {
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auto cv = getConstantIntValue(ofr);
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if (!cv.has_value())
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failed = true;
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return cv.value_or(0);
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});
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if (failed)
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return std::nullopt;
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return res;
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}
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bool isConstantIntValue(OpFoldResult ofr, int64_t value) {
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auto val = getConstantIntValue(ofr);
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return val && *val == value;
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}
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bool areAllConstantIntValue(ArrayRef<OpFoldResult> ofrs, int64_t value) {
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return llvm::all_of(
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ofrs, [&](OpFoldResult ofr) { return isConstantIntValue(ofr, value); });
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}
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bool areConstantIntValues(ArrayRef<OpFoldResult> ofrs,
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ArrayRef<int64_t> values) {
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if (ofrs.size() != values.size())
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return false;
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std::optional<SmallVector<int64_t>> constOfrs = getConstantIntValues(ofrs);
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return constOfrs && llvm::equal(constOfrs.value(), values);
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}
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/// Return true if ofr1 and ofr2 are the same integer constant attribute values
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/// or the same SSA value.
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/// Ignore integer bitwidth and type mismatch that come from the fact there is
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/// no IndexAttr and that IndexType has no bitwidth.
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bool isEqualConstantIntOrValue(OpFoldResult ofr1, OpFoldResult ofr2) {
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auto cst1 = getConstantIntValue(ofr1), cst2 = getConstantIntValue(ofr2);
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if (cst1 && cst2 && *cst1 == *cst2)
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return true;
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auto v1 = llvm::dyn_cast_if_present<Value>(ofr1),
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v2 = llvm::dyn_cast_if_present<Value>(ofr2);
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return v1 && v1 == v2;
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}
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bool isEqualConstantIntOrValueArray(ArrayRef<OpFoldResult> ofrs1,
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ArrayRef<OpFoldResult> ofrs2) {
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if (ofrs1.size() != ofrs2.size())
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return false;
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for (auto [ofr1, ofr2] : llvm::zip_equal(ofrs1, ofrs2))
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if (!isEqualConstantIntOrValue(ofr1, ofr2))
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return false;
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return true;
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}
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/// Return a vector of OpFoldResults with the same size a staticValues, but all
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/// elements for which ShapedType::isDynamic is true, will be replaced by
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/// dynamicValues.
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SmallVector<OpFoldResult> getMixedValues(ArrayRef<int64_t> staticValues,
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ValueRange dynamicValues, Builder &b) {
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SmallVector<OpFoldResult> res;
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res.reserve(staticValues.size());
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unsigned numDynamic = 0;
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unsigned count = static_cast<unsigned>(staticValues.size());
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for (unsigned idx = 0; idx < count; ++idx) {
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int64_t value = staticValues[idx];
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res.push_back(ShapedType::isDynamic(value)
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? OpFoldResult{dynamicValues[numDynamic++]}
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: OpFoldResult{b.getI64IntegerAttr(staticValues[idx])});
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}
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return res;
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}
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/// Decompose a vector of mixed static or dynamic values into the corresponding
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/// pair of arrays. This is the inverse function of `getMixedValues`.
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std::pair<SmallVector<int64_t>, SmallVector<Value>>
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decomposeMixedValues(const SmallVectorImpl<OpFoldResult> &mixedValues) {
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SmallVector<int64_t> staticValues;
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SmallVector<Value> dynamicValues;
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for (const auto &it : mixedValues) {
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if (it.is<Attribute>()) {
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staticValues.push_back(cast<IntegerAttr>(it.get<Attribute>()).getInt());
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} else {
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staticValues.push_back(ShapedType::kDynamic);
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dynamicValues.push_back(it.get<Value>());
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}
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}
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return {staticValues, dynamicValues};
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}
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/// Helper to sort `values` according to matching `keys`.
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template <typename K, typename V>
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static SmallVector<V>
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getValuesSortedByKeyImpl(ArrayRef<K> keys, ArrayRef<V> values,
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llvm::function_ref<bool(K, K)> compare) {
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if (keys.empty())
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return SmallVector<V>{values};
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assert(keys.size() == values.size() && "unexpected mismatching sizes");
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auto indices = llvm::to_vector(llvm::seq<int64_t>(0, values.size()));
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std::sort(indices.begin(), indices.end(),
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[&](int64_t i, int64_t j) { return compare(keys[i], keys[j]); });
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SmallVector<V> res;
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res.reserve(values.size());
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for (int64_t i = 0, e = indices.size(); i < e; ++i)
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res.push_back(values[indices[i]]);
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return res;
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}
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SmallVector<Value>
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getValuesSortedByKey(ArrayRef<Attribute> keys, ArrayRef<Value> values,
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llvm::function_ref<bool(Attribute, Attribute)> compare) {
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return getValuesSortedByKeyImpl(keys, values, compare);
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}
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SmallVector<OpFoldResult>
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getValuesSortedByKey(ArrayRef<Attribute> keys, ArrayRef<OpFoldResult> values,
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llvm::function_ref<bool(Attribute, Attribute)> compare) {
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return getValuesSortedByKeyImpl(keys, values, compare);
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}
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SmallVector<int64_t>
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getValuesSortedByKey(ArrayRef<Attribute> keys, ArrayRef<int64_t> values,
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llvm::function_ref<bool(Attribute, Attribute)> compare) {
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return getValuesSortedByKeyImpl(keys, values, compare);
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}
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/// Return the number of iterations for a loop with a lower bound `lb`, upper
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/// bound `ub` and step `step`.
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std::optional<int64_t> constantTripCount(OpFoldResult lb, OpFoldResult ub,
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OpFoldResult step) {
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if (lb == ub)
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return 0;
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std::optional<int64_t> lbConstant = getConstantIntValue(lb);
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if (!lbConstant)
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return std::nullopt;
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std::optional<int64_t> ubConstant = getConstantIntValue(ub);
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if (!ubConstant)
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return std::nullopt;
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std::optional<int64_t> stepConstant = getConstantIntValue(step);
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if (!stepConstant)
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return std::nullopt;
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return llvm::divideCeilSigned(*ubConstant - *lbConstant, *stepConstant);
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}
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bool hasValidSizesOffsets(SmallVector<int64_t> sizesOrOffsets) {
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return llvm::none_of(sizesOrOffsets, [](int64_t value) {
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return !ShapedType::isDynamic(value) && value < 0;
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});
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}
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bool hasValidStrides(SmallVector<int64_t> strides) {
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return llvm::none_of(strides, [](int64_t value) {
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return !ShapedType::isDynamic(value) && value == 0;
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});
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}
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LogicalResult foldDynamicIndexList(SmallVectorImpl<OpFoldResult> &ofrs,
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bool onlyNonNegative, bool onlyNonZero) {
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bool valuesChanged = false;
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for (OpFoldResult &ofr : ofrs) {
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if (ofr.is<Attribute>())
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continue;
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Attribute attr;
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if (matchPattern(ofr.get<Value>(), m_Constant(&attr))) {
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// Note: All ofrs have index type.
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if (onlyNonNegative && *getConstantIntValue(attr) < 0)
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continue;
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if (onlyNonZero && *getConstantIntValue(attr) == 0)
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continue;
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ofr = attr;
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valuesChanged = true;
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}
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}
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return success(valuesChanged);
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}
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LogicalResult
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foldDynamicOffsetSizeList(SmallVectorImpl<OpFoldResult> &offsetsOrSizes) {
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return foldDynamicIndexList(offsetsOrSizes, /*onlyNonNegative=*/true,
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/*onlyNonZero=*/false);
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}
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LogicalResult foldDynamicStrideList(SmallVectorImpl<OpFoldResult> &strides) {
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return foldDynamicIndexList(strides, /*onlyNonNegative=*/false,
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/*onlyNonZero=*/true);
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}
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} // namespace mlir
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