[llvm] [mlir] [mlir][SCF] Retire SCF-specific `to_memref`/`to_tensor` canonicalization patterns (PR #74551)
Matthias Springer via llvm-commits
llvm-commits at lists.llvm.org
Tue Dec 5 19:46:46 PST 2023
https://github.com/matthias-springer updated https://github.com/llvm/llvm-project/pull/74551
>From a00b999e3b46dbb184c82c773b7455c071c2ec38 Mon Sep 17 00:00:00 2001
From: Matthias Springer <springerm at google.com>
Date: Wed, 6 Dec 2023 12:45:51 +0900
Subject: [PATCH] [mlir][SCF] Retire SCF-specific `to_memref`/`to_tensor`
canonicalization patterns
The partial bufferization framework has been replaced with One-Shot Bufferize. SCF-specific canonicalization patterns for `to_memref`/`to_tensor` are no longer needed.
---
mlir/lib/Dialect/SCF/IR/CMakeLists.txt | 3 +-
mlir/lib/Dialect/SCF/IR/SCF.cpp | 132 +-----------------
mlir/test/Dialect/SCF/canonicalize.mlir | 50 -------
.../llvm-project-overlay/mlir/BUILD.bazel | 1 -
4 files changed, 4 insertions(+), 182 deletions(-)
diff --git a/mlir/lib/Dialect/SCF/IR/CMakeLists.txt b/mlir/lib/Dialect/SCF/IR/CMakeLists.txt
index 9882b843c285e..423e1c3e1e042 100644
--- a/mlir/lib/Dialect/SCF/IR/CMakeLists.txt
+++ b/mlir/lib/Dialect/SCF/IR/CMakeLists.txt
@@ -11,12 +11,13 @@ add_mlir_dialect_library(MLIRSCFDialect
LINK_LIBS PUBLIC
MLIRArithDialect
- MLIRBufferizationDialect
MLIRControlFlowDialect
+ MLIRDialectUtils
MLIRFunctionInterfaces
MLIRIR
MLIRLoopLikeInterface
MLIRSideEffectInterfaces
+ MLIRTensorDialect
MLIRValueBoundsOpInterface
)
diff --git a/mlir/lib/Dialect/SCF/IR/SCF.cpp b/mlir/lib/Dialect/SCF/IR/SCF.cpp
index 3b55704c4ea07..cf807a2adc10e 100644
--- a/mlir/lib/Dialect/SCF/IR/SCF.cpp
+++ b/mlir/lib/Dialect/SCF/IR/SCF.cpp
@@ -9,7 +9,6 @@
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
-#include "mlir/Dialect/Bufferization/IR/Bufferization.h"
#include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/IR/DeviceMappingInterface.h"
@@ -1082,139 +1081,12 @@ struct ForOpTensorCastFolder : public OpRewritePattern<ForOp> {
}
};
-/// Canonicalize the iter_args of an scf::ForOp that involve a
-/// `bufferization.to_tensor` and for which only the last loop iteration is
-/// actually visible outside of the loop. The canonicalization looks for a
-/// pattern such as:
-/// ```
-/// %t0 = ... : tensor_type
-/// %0 = scf.for ... iter_args(%bb0 : %t0) -> (tensor_type) {
-/// ...
-/// // %m is either buffer_cast(%bb00) or defined above the loop
-/// %m... : memref_type
-/// ... // uses of %m with potential inplace updates
-/// %new_tensor = bufferization.to_tensor %m : memref_type
-/// ...
-/// scf.yield %new_tensor : tensor_type
-/// }
-/// ```
-///
-/// `%bb0` may have either 0 or 1 use. If it has 1 use it must be exactly a
-/// `%m = buffer_cast %bb0` op that feeds into the yielded
-/// `bufferization.to_tensor` op.
-///
-/// If no aliasing write to the memref `%m`, from which `%new_tensor`is loaded,
-/// occurs between `bufferization.to_tensor and yield then the value %0
-/// visible outside of the loop is the last `bufferization.to_tensor`
-/// produced in the loop.
-///
-/// For now, we approximate the absence of aliasing by only supporting the case
-/// when the bufferization.to_tensor is the operation immediately preceding
-/// the yield.
-//
-/// The canonicalization rewrites the pattern as:
-/// ```
-/// // %m is either a buffer_cast or defined above
-/// %m... : memref_type
-/// scf.for ... iter_args(%bb0 : %t0) -> (tensor_type) {
-/// ... // uses of %m with potential inplace updates
-/// scf.yield %bb0: tensor_type
-/// }
-/// %0 = bufferization.to_tensor %m : memref_type
-/// ```
-///
-/// A later bbArg canonicalization will further rewrite as:
-/// ```
-/// // %m is either a buffer_cast or defined above
-/// %m... : memref_type
-/// scf.for ... { // no iter_args
-/// ... // uses of %m with potential inplace updates
-/// }
-/// %0 = bufferization.to_tensor %m : memref_type
-/// ```
-struct LastTensorLoadCanonicalization : public OpRewritePattern<ForOp> {
- using OpRewritePattern<ForOp>::OpRewritePattern;
-
- LogicalResult matchAndRewrite(ForOp forOp,
- PatternRewriter &rewriter) const override {
- assert(std::next(forOp.getRegion().begin()) == forOp.getRegion().end() &&
- "unexpected multiple blocks");
-
- Location loc = forOp.getLoc();
- DenseMap<Value, Value> replacements;
- for (BlockArgument bbArg : forOp.getRegionIterArgs()) {
- unsigned idx = bbArg.getArgNumber() - /*numIv=*/1;
- auto yieldOp =
- cast<scf::YieldOp>(forOp.getRegion().front().getTerminator());
- Value yieldVal = yieldOp->getOperand(idx);
- auto tensorLoadOp = yieldVal.getDefiningOp<bufferization::ToTensorOp>();
- bool isTensor = llvm::isa<TensorType>(bbArg.getType());
-
- bufferization::ToMemrefOp tensorToMemref;
- // Either bbArg has no use or it has a single buffer_cast use.
- if (bbArg.hasOneUse())
- tensorToMemref =
- dyn_cast<bufferization::ToMemrefOp>(*bbArg.getUsers().begin());
- if (!isTensor || !tensorLoadOp || (!bbArg.use_empty() && !tensorToMemref))
- continue;
- // If tensorToMemref is present, it must feed into the `ToTensorOp`.
- if (tensorToMemref && tensorLoadOp.getMemref() != tensorToMemref)
- continue;
- // TODO: Any aliasing write of tensorLoadOp.memref() nested under `forOp`
- // must be before `ToTensorOp` in the block so that the lastWrite
- // property is not subject to additional side-effects.
- // For now, we only support the case when ToTensorOp appears
- // immediately before the terminator.
- if (tensorLoadOp->getNextNode() != yieldOp)
- continue;
-
- // Clone the optional tensorToMemref before forOp.
- if (tensorToMemref) {
- rewriter.setInsertionPoint(forOp);
- rewriter.replaceOpWithNewOp<bufferization::ToMemrefOp>(
- tensorToMemref, tensorToMemref.getMemref().getType(),
- tensorToMemref.getTensor());
- }
-
- // Clone the tensorLoad after forOp.
- rewriter.setInsertionPointAfter(forOp);
- Value newTensorLoad = rewriter.create<bufferization::ToTensorOp>(
- loc, tensorLoadOp.getMemref());
- Value forOpResult = forOp.getResult(bbArg.getArgNumber() - /*iv=*/1);
- replacements.insert(std::make_pair(forOpResult, newTensorLoad));
-
- // Make the terminator just yield the bbArg, the old tensorLoadOp + the
- // old bbArg (that is now directly yielded) will canonicalize away.
- rewriter.startRootUpdate(yieldOp);
- yieldOp.setOperand(idx, bbArg);
- rewriter.finalizeRootUpdate(yieldOp);
- }
- if (replacements.empty())
- return failure();
-
- // We want to replace a subset of the results of `forOp`. rewriter.replaceOp
- // replaces the whole op and erase it unconditionally. This is wrong for
- // `forOp` as it generally contains ops with side effects.
- // Instead, use `rewriter.replaceOpWithIf`.
- SmallVector<Value> newResults;
- newResults.reserve(forOp.getNumResults());
- for (Value v : forOp.getResults()) {
- auto it = replacements.find(v);
- newResults.push_back((it != replacements.end()) ? it->second : v);
- }
- unsigned idx = 0;
- rewriter.replaceOpWithIf(forOp, newResults, [&](OpOperand &op) {
- return op.get() != newResults[idx++];
- });
- return success();
- }
-};
} // namespace
void ForOp::getCanonicalizationPatterns(RewritePatternSet &results,
MLIRContext *context) {
- results.add<ForOpIterArgsFolder, SimplifyTrivialLoops,
- LastTensorLoadCanonicalization, ForOpTensorCastFolder>(context);
+ results.add<ForOpIterArgsFolder, SimplifyTrivialLoops, ForOpTensorCastFolder>(
+ context);
}
std::optional<APInt> ForOp::getConstantStep() {
diff --git a/mlir/test/Dialect/SCF/canonicalize.mlir b/mlir/test/Dialect/SCF/canonicalize.mlir
index 9dbf8d5dab11a..41e028028616a 100644
--- a/mlir/test/Dialect/SCF/canonicalize.mlir
+++ b/mlir/test/Dialect/SCF/canonicalize.mlir
@@ -773,56 +773,6 @@ func.func @remove_empty_parallel_loop(%lb: index, %ub: index, %s: index) {
// -----
-func.func private @process(%0 : memref<128x128xf32>)
-func.func private @process_tensor(%0 : tensor<128x128xf32>) -> memref<128x128xf32>
-
-// CHECK-LABEL: last_value
-// CHECK-SAME: %[[T0:[0-9a-z]*]]: tensor<128x128xf32>
-// CHECK-SAME: %[[T1:[0-9a-z]*]]: tensor<128x128xf32>
-// CHECK-SAME: %[[T2:[0-9a-z]*]]: tensor<128x128xf32>
-// CHECK-SAME: %[[M0:[0-9a-z]*]]: memref<128x128xf32>
-func.func @last_value(%t0: tensor<128x128xf32>, %t1: tensor<128x128xf32>,
- %t2: tensor<128x128xf32>, %m0: memref<128x128xf32>,
- %lb : index, %ub : index, %step : index)
- -> (tensor<128x128xf32>, tensor<128x128xf32>, tensor<128x128xf32>)
-{
- // CHECK-NEXT: %[[M1:.*]] = bufferization.to_memref %[[T1]] : memref<128x128xf32>
- // CHECK-NEXT: %[[FOR_RES:.*]] = scf.for {{.*}} iter_args(%[[BBARG_T2:.*]] = %[[T2]]) -> (tensor<128x128xf32>) {
- %0:3 = scf.for %arg0 = %lb to %ub step %step iter_args(%arg1 = %t0, %arg2 = %t1, %arg3 = %t2)
- -> (tensor<128x128xf32>, tensor<128x128xf32>, tensor<128x128xf32>)
- {
- %m1 = bufferization.to_memref %arg2 : memref<128x128xf32>
-
- // CHECK-NEXT: call @process(%[[M0]]) : (memref<128x128xf32>) -> ()
- func.call @process(%m0) : (memref<128x128xf32>) -> ()
-
- // CHECK-NEXT: call @process(%[[M1]]) : (memref<128x128xf32>) -> ()
- func.call @process(%m1) : (memref<128x128xf32>) -> ()
-
- // This does not hoist (fails the bbArg has at most a single check).
- // CHECK-NEXT: %[[T:.*]] = func.call @process_tensor(%[[BBARG_T2]]) : (tensor<128x128xf32>) -> memref<128x128xf32>
- // CHECK-NEXT: %[[YIELD_T:.*]] = bufferization.to_tensor %[[T:.*]]
- %m2 = func.call @process_tensor(%arg3): (tensor<128x128xf32>) -> memref<128x128xf32>
- %3 = bufferization.to_tensor %m2 : memref<128x128xf32>
-
- // All this stuff goes away, incrementally
- %1 = bufferization.to_tensor %m0 : memref<128x128xf32>
- %2 = bufferization.to_tensor %m1 : memref<128x128xf32>
-
- // CHECK-NEXT: scf.yield %[[YIELD_T]] : tensor<128x128xf32>
- scf.yield %1, %2, %3 : tensor<128x128xf32>, tensor<128x128xf32>, tensor<128x128xf32>
-
- // CHECK-NEXT: }
- }
-
- // CHECK-NEXT: %[[R0:.*]] = bufferization.to_tensor %[[M0]] : memref<128x128xf32>
- // CHECK-NEXT: %[[R1:.*]] = bufferization.to_tensor %[[M1]] : memref<128x128xf32>
- // CHECK-NEXT: return %[[R0]], %[[R1]], %[[FOR_RES]] : tensor<128x128xf32>, tensor<128x128xf32>, tensor<128x128xf32>
- return %0#0, %0#1, %0#2 : tensor<128x128xf32>, tensor<128x128xf32>, tensor<128x128xf32>
-}
-
-// -----
-
// CHECK-LABEL: fold_away_iter_with_no_use_and_yielded_input
// CHECK-SAME: %[[A0:[0-9a-z]*]]: i32
func.func @fold_away_iter_with_no_use_and_yielded_input(%arg0 : i32,
diff --git a/utils/bazel/llvm-project-overlay/mlir/BUILD.bazel b/utils/bazel/llvm-project-overlay/mlir/BUILD.bazel
index 4fb6a50a174c2..2a3ebbba02384 100644
--- a/utils/bazel/llvm-project-overlay/mlir/BUILD.bazel
+++ b/utils/bazel/llvm-project-overlay/mlir/BUILD.bazel
@@ -3994,7 +3994,6 @@ cc_library(
deps = [
":ArithDialect",
":ArithUtils",
- ":BufferizationDialect",
":ControlFlowDialect",
":ControlFlowInterfaces",
":DestinationStyleOpInterface",
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