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authorNicolas Vasilache <nicolas.vasilache@gmail.com>2023-05-12 08:43:10 -0700
committerNicolas Vasilache <nicolas.vasilache@gmail.com>2023-05-12 09:27:31 -0700
commit26b5b064f066519096fb556f99b6e2dc163b9283 (patch)
tree87d8e622d485570aa329f1591ce6e792294b857a /mlir/lib
parentad8765a0c8f44311b75d9965472be9aca49a37ab (diff)
downloadllvm-26b5b064f066519096fb556f99b6e2dc163b9283.tar.gz
[mlir][Linalg] NFC - Retire dead FusionOnTensors.cpp
Diffstat (limited to 'mlir/lib')
-rw-r--r--mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt1
-rw-r--r--mlir/lib/Dialect/Linalg/Transforms/FusionOnTensors.cpp417
2 files changed, 0 insertions, 418 deletions
diff --git a/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt b/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
index d3a1a52e7e7a..7877edee6d19 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
+++ b/mlir/lib/Dialect/Linalg/Transforms/CMakeLists.txt
@@ -14,7 +14,6 @@ add_mlir_dialect_library(MLIRLinalgTransforms
EraseUnusedOperandsAndResults.cpp
FusePadOpWithLinalgProducer.cpp
Fusion.cpp
- FusionOnTensors.cpp
Generalization.cpp
Hoisting.cpp
HoistPadding.cpp
diff --git a/mlir/lib/Dialect/Linalg/Transforms/FusionOnTensors.cpp b/mlir/lib/Dialect/Linalg/Transforms/FusionOnTensors.cpp
deleted file mode 100644
index 87aade3a3eec..000000000000
--- a/mlir/lib/Dialect/Linalg/Transforms/FusionOnTensors.cpp
+++ /dev/null
@@ -1,417 +0,0 @@
-//===- FusionOnTensors.cpp - Implementation of linalg Fusion --------------===//
-//
-// 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 linalg fusion on tensors
-//
-//===----------------------------------------------------------------------===//
-
-#include "mlir/Analysis/SliceAnalysis.h"
-#include "mlir/Dialect/Affine/IR/AffineOps.h"
-#include "mlir/Dialect/Linalg/IR/Linalg.h"
-#include "mlir/Dialect/Linalg/Passes.h"
-#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
-#include "mlir/Dialect/Linalg/Utils/Utils.h"
-#include "mlir/Dialect/Tensor/IR/Tensor.h"
-#include "mlir/Dialect/Utils/IndexingUtils.h"
-#include "mlir/IR/AffineExpr.h"
-#include "mlir/IR/AffineMap.h"
-#include "mlir/Support/LLVM.h"
-#include <optional>
-
-using namespace mlir;
-using namespace linalg;
-
-//===----------------------------------------------------------------------===//
-// StructuredOp specific helpers.
-//===----------------------------------------------------------------------===//
-
-/// Returns the tiled slice dimensions given the tiled consumer loop dimensions.
-/// The slice defines a hyper rectangular iteration space and fusing the
-/// producer is always possible. However, depending on the consumer indexing
-/// map, not all slice elements may be consumed and the tiles may overlap. In
-/// these cases, fusion introduces redundant computation.
-static SmallVector<int64_t> getTiledSliceDims(OpOperand *consumerOperand,
- ArrayRef<int64_t> tiledLoopDims) {
- // Get the consumer operand indexing map.
- auto consumerOp = cast<LinalgOp>(consumerOperand->getOwner());
- AffineMap indexingMap = consumerOp.getMatchingIndexingMap(consumerOperand);
-
- // Search the slice dimensions tiled by a tile loop dimension.
- DenseSet<int64_t> tiledSliceDimIndices;
- for (const auto &en : enumerate(indexingMap.getResults())) {
- for (auto tiledLoopDim : tiledLoopDims) {
- if (en.value().isFunctionOfDim(tiledLoopDim))
- tiledSliceDimIndices.insert(en.index());
- }
- }
- return {tiledSliceDimIndices.begin(), tiledSliceDimIndices.end()};
-}
-
-/// Given a vector of `tiledSliceDimIndices` that represent the tiled dimensions
-/// of the producer result slice returns the tiled producer loop dimensions.
-/// Example:
-/// ```
-/// %res = linalg.fill(%cst, %input)
-/// scf.for %i
-/// scf.for %j
-/// %slice = tensor.extract_slice %res[%i, %j]
-/// ```
-/// getTiledProducerLoops(%res, [0, 1]) returns the loop indices [0, 1].
-static SmallVector<int64_t>
-getTiledProducerLoops(OpResult producerResult,
- ArrayRef<int64_t> tiledSliceDimIndices) {
- auto producerOp = cast<LinalgOp>(producerResult.getOwner());
-
- // Get the indexing map of the `producerOp` output operand that matches
- // ´producerResult´.
- AffineMap producerIndexingMap = producerOp.getMatchingIndexingMap(
- producerOp.getDpsInitOperand(producerResult.getResultNumber()));
-
- // Keep only the tiled result slice dimensions of `producerIndexingMap`.
- AffineMap tiledProducerIndexingSubMap =
- producerIndexingMap.getSubMap(SmallVector<unsigned>(
- tiledSliceDimIndices.begin(), tiledSliceDimIndices.end()));
-
- // Compute the producer loop indices mapped to the tiled result slice
- // dimensions. As the output indexing map of structured operations are
- // projected permutations, `tiledProducerIndexingSubMap` has to be a
- // projected permutation as well. We can thus obtain the producer loop indices
- // by getting the positions of the result dimensions.
- // Example:
- // (d0, d1, d2) -> (d0, d2) has the result positions [0, 2].
- assert(tiledProducerIndexingSubMap.isProjectedPermutation() &&
- "expect slice and producer loop dimensions map one-to-one");
- SmallVector<int64_t> tiledProducerLoopIndices;
- llvm::transform(
- llvm::seq<unsigned>(0, tiledProducerIndexingSubMap.getNumResults()),
- std::back_inserter(tiledProducerLoopIndices), [&](unsigned idx) {
- return tiledProducerIndexingSubMap.getDimPosition(idx);
- });
-
- return tiledProducerLoopIndices;
-}
-
-/// Returns the producer fused in place of `sliceOp`. Tile the producer operands
-/// along the `tiledSliceDimIndices` and clone the producer. Consider the case
-/// of fusion of an output tensor:
-/// ```
-/// %1 = producer ins(...) outs(%0)
-/// %2 = consumer ins(...) outs(%1)
-/// ```
-/// When consumer is tiled, %1 appears in the loop iter_args:
-/// ```
-/// %1 = producer ins(...) outs(%0)
-/// %2 = scf.for ... iter_args(%1) .. (%bbarg) {
-/// %t1 = tensor.extract_slice %bbarg[..]
-/// %t2 = consumer ins(...) outs(%t1)
-/// %r = tensor.insert_slice %t2, %bbarg[...]
-/// }
-/// ```
-/// Fusing %1 into the loop requires updating iter_args(%1) to iter_args(%0):
-/// ```
-/// %2 = scf.for ... iter_args(%0) .. (%bbarg) {
-/// %t0 = tensor.extract_slice %bbarg[..]
-/// %t1 = producer ins(...) outs(%t0)
-/// %t2 = consumer ins(...) outs(%t1)
-/// %r = tensor.insert_slice %t2, %bbarg[...]
-/// }
-/// ```
-/// This transformation is only valid if %bbarg is exclusively used by the
-/// output ExtractSliceOp / InsertSliceOp pair, which is checked by the
-/// `fuseProducer` method.
-/// TODO: instead of check and failure, insert new iter_args each time a
-/// producer is fused into a consumer and fold away unused iter_args.
-static LinalgOp getTiledProducer(OpBuilder &b, OpResult producerResult,
- tensor::ExtractSliceOp sliceOp,
- ArrayRef<int64_t> tiledSliceDimIndices,
- ArrayRef<int64_t> tiledProducerLoopIndices,
- OpOperand *iterArg) {
- // Clone the producer after `sliceOp` since the slice may be reused to pass in
- // the producer result.
- OpBuilder::InsertionGuard guard(b);
- b.setInsertionPointAfter(sliceOp);
-
- // Get the producer.
- auto producerOp = cast<LinalgOp>(producerResult.getOwner());
- Location loc = producerOp.getLoc();
-
- // Obtain the `producerOp` loop bounds and the `sliceOp` ranges.
- SmallVector<OpFoldResult> producerLoopBounds;
- llvm::transform(producerOp.createLoopRanges(b, loc),
- std::back_inserter(producerLoopBounds),
- [&](Range range) { return range.size; });
- SmallVector<Range> sliceOpRanges = sliceOp.getOrCreateRanges(b, loc);
-
- // Tile the producer operands given the `sliceOp` ranges. Iterate the
- // `tiledSliceDimIndices` and store the tile offset and size for the tiled
- // slice dimension.
- SmallVector<OpFoldResult> tileIvs(producerOp.getNumLoops(), nullptr);
- SmallVector<OpFoldResult> tileSizes(producerOp.getNumLoops(),
- b.getIndexAttr(0));
- SmallVector<OpFoldResult> allIvs(producerOp.getNumLoops(), nullptr);
- for (auto it : zip(tiledSliceDimIndices, tiledProducerLoopIndices)) {
- int64_t tiledSliceDim = std::get<0>(it);
- int64_t tiledProducerLoop = std::get<1>(it);
- tileIvs[tiledProducerLoop] = sliceOpRanges[tiledSliceDim].offset;
- tileSizes[tiledProducerLoop] = sliceOpRanges[tiledSliceDim].size;
- allIvs[tiledProducerLoop] = tileIvs[tiledProducerLoop];
- }
- erase_value(tileIvs, OpFoldResult());
- SmallVector<Value> tiledOperands = producerOp->getOperands();
- tiledOperands = makeTiledShapes(b, loc, producerOp, tiledOperands, tileIvs,
- tileSizes, producerLoopBounds,
- /**omitPartialTileCheck=*/false);
-
- // Output fusion has to update the iteration arguments of the tile loop nest.
- // In particular, the iteration argument of the outermost tile loop needs to
- // be set to the producer output instead of the producer result and `clonedOp`
- // shall use the existing `sliceOp` result instead of the tiled producer
- // output operand.
- if (iterArg) {
- OpOperand *outputOperand =
- producerOp.getDpsInitOperand(producerResult.getResultNumber());
- iterArg->set(outputOperand->get());
- tiledOperands[outputOperand->getOperandNumber()] = sliceOp.getResult();
- }
-
- // Clone the producer using the tiled producer operands.
- TypeRange resultTypes = ValueRange(tiledOperands)
- .take_back(producerOp.getNumDpsInits())
- .getTypes();
- LinalgOp clonedOp = clone(b, producerOp, resultTypes, tiledOperands);
-
- // Shift all IndexOp results by the tile offset.
- offsetIndices(b, clonedOp, allIvs);
-
- return clonedOp;
-}
-
-//===----------------------------------------------------------------------===//
-// TileLoopNest specific helpers.
-//===----------------------------------------------------------------------===//
-
-bool TileLoopNest::isEmpty() { return tileLoopOps.empty(); }
-
-bool TileLoopNest::isValid() {
- // Check if `rootOp` has been tiled at least once.
- if (isEmpty() || tiledRootAndFusedOpsLoops.count(rootOp) == 0)
- return false;
-
- // Check if the number of loop operations and dimensions match.
- if (tileLoopOps.size() != tiledRootAndFusedOpsLoops[rootOp].size())
- return false;
-
- // Check if the innermost tile loop is the parent of `tiledOp`.
- if (rootOp->getParentOp() != tileLoopOps.back())
- return false;
-
- // Check if the tile loops are directly nested.
- return std::adjacent_find(tileLoopOps.begin(), tileLoopOps.end(),
- [](Operation *op1, Operation *op2) {
- return op1 != op2->getParentOp();
- }) == tileLoopOps.end();
-}
-
-SmallVector<BlockArgument> TileLoopNest::getTiedBBArgs(BlockArgument bbArg) {
- assert(bbArg && "expect the block argument to be non-zero");
- SmallVector<BlockArgument> bbArgs;
-
- // Search all tile loop block arguments from inner to outer.
- for (auto tileLoop : reverse(tileLoopOps)) {
- if (bbArg.getOwner()->getParentOp() != tileLoop)
- return {};
- bbArgs.push_back(bbArg);
- OpOperand *iterArg = &tileLoop.getOpOperandForRegionIterArg(bbArg);
- bbArg = dyn_cast<BlockArgument>(iterArg->get());
- }
-
- // Reverse the block arguments to order them from outer to inner.
- return {bbArgs.rbegin(), bbArgs.rend()};
-}
-
-OpOperand *TileLoopNest::getTiedIterArg(BlockArgument bbArg) {
- // Search all block arguments and return the matching iteration argument.
- SmallVector<BlockArgument> bbArgs = getTiedBBArgs(bbArg);
- if (bbArgs.size() != tileLoopOps.size())
- return nullptr;
- return &tileLoopOps.front().getOpOperandForRegionIterArg(bbArgs.front());
-}
-
-bool TileLoopNest::hasOtherUses(BlockArgument bbArg,
- tensor::ExtractSliceOp sliceOp) {
- // Check the innermost block argument is either used by the ExtractSliceOp
- // `sliceOp`, the matching InsertSliceOp, or by a DimOp. Handle other uses
- // conservatively.
- for (Operation *op : bbArg.getUsers()) {
- if (!isa<tensor::DimOp, tensor::InsertSliceOp, tensor::ExtractSliceOp>(op))
- return false;
- if (auto extractSliceOp = dyn_cast<tensor::ExtractSliceOp>(op)) {
- if (extractSliceOp != sliceOp)
- return false;
- }
- if (auto insertSliceOp = dyn_cast<tensor::InsertSliceOp>(op)) {
- SetVector<Operation *> backwardSlice;
- getBackwardSlice(insertSliceOp.getSource(), &backwardSlice,
- [](Operation *op) {
- return isa<LinalgOp, tensor::InsertSliceOp>(op);
- });
- if (backwardSlice.empty() || backwardSlice.front() != sliceOp)
- return false;
- }
- }
-
- // Check the block arguments, except for the innermost one, have one use.
- SmallVector<BlockArgument> bbArgs = getTiedBBArgs(bbArg);
- return !all_of(bbArgs, [&](BlockArgument bbArg) {
- return bbArg.hasOneUse() || bbArg == bbArgs.back();
- });
-}
-
-LogicalResult TileLoopNest::tileRootOp(
- OpBuilder &b, ArrayRef<int64_t> tileSizes,
- ArrayRef<int64_t> tileInterchange,
- std::optional<LinalgLoopDistributionOptions> tileDistribution) {
- // Exit if all tile sizes are zero.
- if (tileSizes.size() == static_cast<size_t>(count(tileSizes, 0)))
- return success();
-
- // Tile the root operation.
- LinalgTilingOptions tilingOptions;
- tilingOptions = tilingOptions
- .setInterchange(SmallVector<unsigned>(
- tileInterchange.begin(), tileInterchange.end()))
- .setTileSizes(tileSizes)
- .setLoopType(LinalgTilingLoopType::Loops);
- if (tileDistribution)
- tilingOptions = tilingOptions.setDistributionOptions(*tileDistribution);
-
- // TODO: Propagate RewriterBase everywhere.
- IRRewriter rewriter(b);
- FailureOr<TiledLinalgOp> tiledRootOp =
- tileLinalgOp(rewriter, rootOp, tilingOptions);
-
- // Exit if tiling the root operation fails.
- if (failed(tiledRootOp))
- return failure();
-
- // Replace all uses of the root operation if it has been tiled before. All
- // uses of the original untiled root operation are updated by the calling pass
- // or pattern.
- if (!isEmpty())
- rootOp->replaceAllUsesWith(tiledRootOp->tensorResults);
-
- // Transfer the stored `rootOp` loop dimensions if it has been tiled before.
- if (tiledRootAndFusedOpsLoops.count(rootOp) != 0) {
- tiledRootAndFusedOpsLoops[tiledRootOp->op] =
- tiledRootAndFusedOpsLoops[rootOp];
- }
-
- // Update the root operation and append the loops and tile loop dimensions.
- rootOp = tiledRootOp->op;
- tileLoopOps.append(tiledRootOp->loops.begin(), tiledRootOp->loops.end());
- for (const auto &en : enumerate(tileSizes)) {
- // Copy only the tiled loop dimensions with non-zero tile size.
- if (en.value() == 0)
- continue;
- tiledRootAndFusedOpsLoops[rootOp].push_back(tileInterchange[en.index()]);
- }
- assert(isValid() && "expect tile loop nest to be valid after tiling");
- return success();
-}
-
-FailureOr<LinalgOp> TileLoopNest::fuseProducer(OpBuilder &b,
- OpOperand *consumerOpOperand) {
- // Check if the consumer has been tiled before. For example, it may not have
- // been tiled if the outermost tile loop is a reduction loop.
- if (tiledRootAndFusedOpsLoops.count(consumerOpOperand->getOwner()) == 0)
- return failure();
-
- assert(this->isValid() &&
- "expect the tile loop nest to satisfy all invariants");
-
- // Check the tile loop nest is non-empty.
- if (isEmpty())
- return failure();
-
- // Check `consumerOpOperand` is defined by an ExtractSliceOp.
- auto sliceOp =
- consumerOpOperand->get().getDefiningOp<tensor::ExtractSliceOp>();
- if (!sliceOp)
- return failure();
-
- // Check `sliceOp` and `consumerOp` are in the same block.
- auto consumerOp = cast<LinalgOp>(consumerOpOperand->getOwner());
- if (sliceOp->getBlock() != rootOp->getBlock() ||
- consumerOp->getBlock() != rootOp->getBlock())
- return failure();
-
- // Check `consumerOpOperand` is not shape-only to avoid fusion if the data is
- // not used by the `consumerOp` computation.
- BlockArgument bbArg = consumerOp.getMatchingBlockArgument(consumerOpOperand);
- if (bbArg.getUses().empty())
- return failure();
-
- // Check if the producer is a LinalgOp possibly passed by iteration argument.
- OpOperand *iterArg = nullptr;
- auto producerResult = dyn_cast<OpResult>(sliceOp.getSource());
- if (auto bbArg = dyn_cast<BlockArgument>(sliceOp.getSource())) {
- iterArg = getTiedIterArg(bbArg);
- // Check the iteration argument may be used to pass in the producer output.
- if (!iterArg || hasOtherUses(bbArg, sliceOp))
- return failure();
- producerResult = dyn_cast<OpResult>(iterArg->get());
- }
- if (!producerResult || !isa<LinalgOp>(producerResult.getOwner()))
- return failure();
-
- // Compute the tiled producer slice dimensions given the tiled consumer loops.
- SmallVector<int64_t> tiledSliceDimIndices = getTiledSliceDims(
- consumerOpOperand, tiledRootAndFusedOpsLoops[consumerOp]);
- if (tiledSliceDimIndices.empty())
- return failure();
-
- // Compute the tiled producer loop indices.
- SmallVector<int64_t> tiledProducerLoopIndices =
- getTiledProducerLoops(producerResult, tiledSliceDimIndices);
-
- // Tile the producer operands and clone the producer in place of `sliceOp`.
- LinalgOp clonedOp =
- getTiledProducer(b, producerResult, sliceOp, tiledSliceDimIndices,
- tiledProducerLoopIndices, iterArg);
- tiledRootAndFusedOpsLoops[clonedOp] = tiledProducerLoopIndices;
-
- // Cast the `clonedOp` result to gap type mismatches before canonicalization.
- Type consumerOperandType = consumerOpOperand->get().getType();
- Value newResult = clonedOp->getResult(producerResult.getResultNumber());
- if (newResult.getType() != consumerOperandType) {
- OpBuilder::InsertionGuard guard(b);
- b.setInsertionPointAfter(clonedOp);
- newResult = b.create<tensor::CastOp>(producerResult.getLoc(),
- consumerOperandType, newResult);
- }
-
- // Replace the `sliceOp` uses except for the `clonedOp` output uses.
- sliceOp.getResult().replaceAllUsesExcept(newResult, clonedOp);
- return clonedOp;
-}
-
-ValueRange TileLoopNest::getRootOpReplacementResults() {
- assert(!isEmpty() && "expect tile loop nest to be non-empty");
- return tileLoopOps.front()->getOpResults();
-}
-
-SmallVector<LinalgOp> TileLoopNest::getAllTiledAndFusedOps() {
- SmallVector<LinalgOp> result;
- for (const auto &kvp : tiledRootAndFusedOpsLoops) {
- auto linalgOp = dyn_cast<LinalgOp>(kvp.getFirst());
- assert(linalgOp &&
- "expect all tiled and fused operations are linalg operations");
- result.push_back(linalgOp);
- }
- return result;
-}