[mlir][linalg][nfc] Update "pack-dynamic-inner-tile.mlir" #117533

banach-space · 2024-11-25T09:46:17Z

Builds on:

[mlir][linalg] Extract GeneralizePadOpPattern into a standalone transformation #117329: Extract GeneralizePadOpPattern into a standalone transformation.
[mlir] Add apply_patterns.linalg.generalize_pack_unpack TD Op #116373: Update pack-dynamic-inner-tile.mlir.

This update adds vectorization to the "pack-dynamic-inner-tile.mlir"
pipeline.

The pipeline first decomposes tensor.pack into tensor.pad and then
into linalg.fill (#117329). Next,
linalg.fill is vectorized, with vector sizes matching the inner tile sizes
of the original tensor.pack.

llvmbot · 2024-11-25T09:46:53Z

@llvm/pr-subscribers-mlir-linalg

@llvm/pr-subscribers-mlir

Author: Andrzej Warzyński (banach-space)

Changes

[mlir][linalg] Extract GeneralizePadOpPattern into a standalone transformation
[mlir][linalg][nfc] Update "pack-dynamic-inner-tile.mlir"

Full diff: https://github.com/llvm/llvm-project/pull/117533.diff

10 Files Affected:

(modified) mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td (+11)
(modified) mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h (+6-2)
(modified) mlir/lib/Conversion/TensorToLinalg/TensorToLinalg.cpp (+3-1)
(modified) mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp (+10-1)
(modified) mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp (+7-3)
(modified) mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp (-6)
(renamed) mlir/test/Dialect/Linalg/decompose-pad-tensor.mlir (+1-1)
(modified) mlir/test/Dialect/Linalg/vectorization-pad-patterns.mlir (+6)
(modified) mlir/test/Integration/Dialect/Linalg/CPU/pack-dynamic-inner-tile.mlir (+30-11)
(modified) mlir/test/lib/Dialect/Linalg/TestLinalgTransforms.cpp (+6-6)

diff --git a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
index e3084530bd11b5..dc10f3a1c58ae3 100644
--- a/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td
@@ -52,6 +52,17 @@ def ApplyDecomposeTensorPackUnpackPatternsOp
   let assemblyFormat = "attr-dict";
 }
 
+def ApplyDecomposeTensorPadPatternsOp
+    : Op<Transform_Dialect, "apply_patterns.linalg.decompose_pad",
+         [DeclareOpInterfaceMethods<PatternDescriptorOpInterface>]> {
+  let description = [{
+    Collect patterns to decompose tensor.pad into e.g. tensor::EmptyOp,
+    linalg::FillOp and tensor::InsertSliceOp.
+  }];
+
+  let assemblyFormat = "attr-dict";
+}
+
 def ApplyFoldUnitExtentDimsViaReshapesPatternsOp : Op<Transform_Dialect,
     "apply_patterns.linalg.fold_unit_extent_dims_via_reshapes",
     [DeclareOpInterfaceMethods<PatternDescriptorOpInterface>]> {
diff --git a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
index 51967f83fee377..3c160d55a38e75 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
@@ -1503,8 +1503,8 @@ using OptimizeCopyFn =
 
 /// Rewrite a tensor::PadOp into a sequence of EmptyOp, FillOp and
 /// InsertSliceOp. For now, only constant padding values are supported.
-struct GeneralizePadOpPattern : public OpRewritePattern<tensor::PadOp> {
-  GeneralizePadOpPattern(MLIRContext *context, PatternBenefit benefit = 1)
+struct DecomposePadOpPattern : public OpRewritePattern<tensor::PadOp> {
+  DecomposePadOpPattern(MLIRContext *context, PatternBenefit benefit = 1)
       : OpRewritePattern<tensor::PadOp>(context, benefit) {}
   LogicalResult matchAndRewrite(tensor::PadOp padOp,
                                 PatternRewriter &rewriter) const override;
@@ -1688,6 +1688,10 @@ void populateDecomposeConvolutionPatterns(RewritePatternSet &patterns,
 /// outer dims to be unit.
 void populateDecomposePackUnpackPatterns(RewritePatternSet &patterns);
 
+/// Populates patterns to decompose tensor.pad into e.g.
+/// tensor.empty, linalg.fill, tensor.insert_slice.
+void populateDecomposePadPatterns(RewritePatternSet &patterns);
+
 /// Populates patterns to transform linalg.conv_2d_xxx operations into
 /// linalg.generic (for img2col packing) and linalg.matmul.
 /// \see rewriteInIm2Col for more details.
diff --git a/mlir/lib/Conversion/TensorToLinalg/TensorToLinalg.cpp b/mlir/lib/Conversion/TensorToLinalg/TensorToLinalg.cpp
index 5bb79d4bc84e2b..b0ca0ca13d0624 100644
--- a/mlir/lib/Conversion/TensorToLinalg/TensorToLinalg.cpp
+++ b/mlir/lib/Conversion/TensorToLinalg/TensorToLinalg.cpp
@@ -25,5 +25,7 @@ using namespace mlir;
 //===----------------------------------------------------------------------===//
 
 void mlir::populateTensorToLinalgPatterns(RewritePatternSet &patterns) {
-  patterns.add<mlir::linalg::GeneralizePadOpPattern>(patterns.getContext());
+  // TODO: Add the remaining patterns, e.g. to decompose Pack/Unpack Ops.
+  // Alternatively, delete this file.
+  patterns.add<mlir::linalg::DecomposePadOpPattern>(patterns.getContext());
 }
diff --git a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
index ada80deacfdbfe..e08be7d2ebd6ae 100644
--- a/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
+++ b/mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
@@ -234,6 +234,11 @@ void transform::ApplyDecomposeTensorPackUnpackPatternsOp::populatePatterns(
   linalg::populateDecomposePackUnpackPatterns(patterns);
 }
 
+void transform::ApplyDecomposeTensorPadPatternsOp::populatePatterns(
+    RewritePatternSet &patterns) {
+  linalg::populateDecomposePadPatterns(patterns);
+}
+
 void transform::ApplyFoldUnitExtentDimsViaReshapesPatternsOp::populatePatterns(
     RewritePatternSet &patterns) {
   linalg::ControlDropUnitDims options;
@@ -3491,8 +3496,12 @@ transform::VectorizeChildrenAndApplyPatternsOp::applyToOne(
   // Add misc. vectorization patterns (e.g. for tensor.insert_slice)
   linalg::populateInsertSliceVectorizationPatterns(patterns);
 
-  if (getVectorizePadding())
+  if (getVectorizePadding()) {
     linalg::populatePadOpVectorizationPatterns(patterns);
+    // This creates an alternative path for lowering tensor.pad - by
+    // decomposing it into e.g. linalg.fill.
+    linalg::populateDecomposePadPatterns(patterns);
+  }
   vector::populateVectorStepLoweringPatterns(patterns);
 
   TrackingListener listener(state, *this);
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
index d92543d7264625..c3e176299317ef 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
@@ -921,7 +921,7 @@ LogicalResult mlir::linalg::CopyVectorizationPattern::matchAndRewrite(
 
 /// Filling `dest` using FillOp constant padding value if possible.
 /// Otherwise, generate a tensor::GenerateOp.
-Value GeneralizePadOpPattern::createFillOrGenerateOp(
+Value DecomposePadOpPattern::createFillOrGenerateOp(
     RewriterBase &rewriter, tensor::PadOp padOp, Value dest,
     const SmallVector<Value> &dynSizes) const {
   auto padValue = padOp.getConstantPaddingValue();
@@ -938,8 +938,8 @@ Value GeneralizePadOpPattern::createFillOrGenerateOp(
 }
 
 LogicalResult
-GeneralizePadOpPattern::matchAndRewrite(tensor::PadOp padOp,
-                                        PatternRewriter &rewriter) const {
+DecomposePadOpPattern::matchAndRewrite(tensor::PadOp padOp,
+                                       PatternRewriter &rewriter) const {
   // Given an OpFoldResult, return an index-typed value.
   auto getIdxValue = [&](OpFoldResult ofr) {
     if (auto val = llvm::dyn_cast_if_present<Value>(ofr))
@@ -1623,3 +1623,7 @@ void linalg::populateDecomposePackUnpackPatterns(RewritePatternSet &patterns) {
   // TODO: Add and test patterns for tensor.unpack
   patterns.add<DecomposeOuterUnitDimsPackOpPattern>(patterns.getContext());
 }
+
+void linalg::populateDecomposePadPatterns(RewritePatternSet &patterns) {
+  patterns.add<DecomposePadOpPattern>(patterns.getContext());
+}
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
index 23b46a2ee55f8d..06bb6c0fb1cac9 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
@@ -2770,12 +2770,6 @@ void mlir::linalg::populateInsertSliceVectorizationPatterns(
 
 void mlir::linalg::populatePadOpVectorizationPatterns(
     RewritePatternSet &patterns, PatternBenefit baseBenefit) {
-  // TODO: The following pattern implements "decomposition" and
-  // optional "vectorization". Seperate "decomposition" into a sepereate
-  // pre-processing pattern group.
-  patterns.add<GeneralizePadOpPattern>(patterns.getContext(), baseBenefit);
-
-  // Try these specialized patterns first before resorting to the generic one.
   patterns.add<PadOpVectorizationWithTransferReadPattern,
                PadOpVectorizationWithTransferWritePattern,
                PadOpVectorizationWithInsertSlicePattern>(
diff --git a/mlir/test/Dialect/Linalg/generalize-pad-tensor.mlir b/mlir/test/Dialect/Linalg/decompose-pad-tensor.mlir
similarity index 98%
rename from mlir/test/Dialect/Linalg/generalize-pad-tensor.mlir
rename to mlir/test/Dialect/Linalg/decompose-pad-tensor.mlir
index 2beab31b613d54..184361dfb30dfd 100644
--- a/mlir/test/Dialect/Linalg/generalize-pad-tensor.mlir
+++ b/mlir/test/Dialect/Linalg/decompose-pad-tensor.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt -split-input-file --test-linalg-transform-patterns="test-generalize-pad-tensor"  %s | FileCheck %s
+// RUN: mlir-opt -split-input-file --test-linalg-transform-patterns="test-decompose-pad-tensor"  %s | FileCheck %s
 
 // CHECK-LABEL:   func @generalize_pad_tensor_static_shape(
 // CHECK-SAME:                                             %[[IN:.*]]: tensor<1x28x28x1xf32>) -> tensor<1x32x32x1xf32> {
diff --git a/mlir/test/Dialect/Linalg/vectorization-pad-patterns.mlir b/mlir/test/Dialect/Linalg/vectorization-pad-patterns.mlir
index 640de85cc5f12e..41e480648177f5 100644
--- a/mlir/test/Dialect/Linalg/vectorization-pad-patterns.mlir
+++ b/mlir/test/Dialect/Linalg/vectorization-pad-patterns.mlir
@@ -202,6 +202,8 @@ module attributes {transform.with_named_sequence} {
     %func_op = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.op<"func.func">
 
     transform.apply_patterns to %func_op {
+      // TODO: Split into two tests, one for each pattern
+      transform.apply_patterns.linalg.decompose_pad
       transform.apply_patterns.linalg.pad_vectorization
     } : !transform.op<"func.func">
     transform.yield
@@ -236,6 +238,8 @@ module attributes {transform.with_named_sequence} {
     %func_op = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.op<"func.func">
 
     transform.apply_patterns to %func_op {
+      // TODO: Split into two tests, one for each pattern
+      transform.apply_patterns.linalg.decompose_pad
       transform.apply_patterns.linalg.pad_vectorization
     } : !transform.op<"func.func">
     transform.yield
@@ -270,6 +274,8 @@ module attributes {transform.with_named_sequence} {
     %func_op = transform.structured.match ops{["func.func"]} in %arg1 : (!transform.any_op) -> !transform.op<"func.func">
 
     transform.apply_patterns to %func_op {
+      // TODO: Split into two tests, one for each pattern
+      transform.apply_patterns.linalg.decompose_pad
       transform.apply_patterns.linalg.pad_vectorization
     } : !transform.op<"func.func">
     transform.yield
diff --git a/mlir/test/Integration/Dialect/Linalg/CPU/pack-dynamic-inner-tile.mlir b/mlir/test/Integration/Dialect/Linalg/CPU/pack-dynamic-inner-tile.mlir
index 32b7247e60d622..0d2fd977c8d557 100644
--- a/mlir/test/Integration/Dialect/Linalg/CPU/pack-dynamic-inner-tile.mlir
+++ b/mlir/test/Integration/Dialect/Linalg/CPU/pack-dynamic-inner-tile.mlir
@@ -10,10 +10,6 @@
 
 /// End-to-end test for tensor.pack where one of the inner tile sizes is
 /// dynamic.
-///
-/// Note, ATM this is a relatively simple example, with no vectorization and
-/// the dynamic tile size being a compile-time constant. The intention is to
-/// incrementally expand the config to something much more complex.
 
 func.func @main() {
   // Allocate and initialise the inputs
@@ -89,26 +85,49 @@ module @transforms attributes { transform.with_named_sequence } {
     %tiled_pack_op_p, %loops:2 = transform.structured.tile_using_for %pack tile_sizes [1, 1]
        : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
 
-    // 2. Decompose the tiled Op into (trimmed for brevity):
+    // 2. Decompose the tiled pack Op into (trimmed for brevity):
     //
     //  %padded = tensor.pad %slice_of_A (..) :
     //      tensor<?x?xi32> to tensor<8x1xi32>
     //  %inserted_slice = tensor.insert_slice %padded into %slice_of_A_pack (...) :
     //      tensor<8x1xi32> into tensor<1x1x?x1xi32>
     //
-    // NOTE: no tile is transposed, hence no linalg.transpose
-    %func_1 = transform.get_parent_op %tiled_pack_op_p {isolated_from_above} : (!transform.any_op) -> !transform.any_op
-    transform.apply_patterns to %func_1 {
+    // (NOTE: no tile is transposed, hence no linalg.transpose)
+    //
+    // This is followed by this decomposition of the pad Op:
+    //
+    //  %c123_i32 = arith.constant 123 : i32
+    //  %slice_of_A = tensor.extract_slice %A[%3, %arg3] [%4, %5] [1, 1] :
+    //    tensor<7x16xi32> to tensor<?x?xi32>
+    //  %empty = tensor.empty() : tensor<8x1xi32>
+    //  %fill = linalg.fill ins(%c123_i32 : i32) outs(%empty :
+    //    tensor<8x1xi32>) -> tensor<8x1xi32>
+    //  %inserted_slice = tensor.insert_slice %slice_of_A into %fill[0, 0] [%4, %5] [1, 1] :
+    //    tensor<?x?xi32> into tensor<8x1xi32>
+    //
+    %func_op = transform.get_parent_op %tiled_pack_op_p {isolated_from_above} : (!transform.any_op) -> !transform.op<"func.func">
+    transform.apply_patterns to %func_op {
       transform.apply_patterns.linalg.decompose_pack_unpack
-    } : !transform.any_op
+      transform.apply_patterns.linalg.decompose_pad
+    } : !transform.op<"func.func">
+
+    // 3. Vectorize linalg.fill.
+    // Vector sizes match the inner tiles in the payload IR.
+    %fill = transform.structured.match ops{["linalg.fill"]} in %func_op : (!transform.op<"func.func">) -> !transform.any_op
+    transform.structured.vectorize %fill vector_sizes [8, 1] : !transform.any_op
+
+    transform.apply_patterns to %func_op {
+      transform.apply_patterns.tensor.fold_tensor_subset_ops
+      transform.apply_patterns.canonicalization
+    } : !transform.op<"func.func">
 
     // 3. Bufferize before lowering to LLVM
     %bufferize = transform.bufferization.one_shot_bufferize %module
       {bufferize_function_boundaries=true} : (!transform.any_op) -> !transform.any_op
 
     // 4. Canonicalize
-    %func_2 = transform.structured.match ops{["func.func"]} in %bufferize : (!transform.any_op) -> !transform.op<"func.func">
-    transform.apply_patterns to %func_2 {
+    %func_op_bufferized = transform.structured.match ops{["func.func"]} in %bufferize : (!transform.any_op) -> !transform.op<"func.func">
+    transform.apply_patterns to %func_op_bufferized {
       transform.apply_patterns.canonicalization
     } : !transform.op<"func.func">
 
diff --git a/mlir/test/lib/Dialect/Linalg/TestLinalgTransforms.cpp b/mlir/test/lib/Dialect/Linalg/TestLinalgTransforms.cpp
index c65e68eaf31f09..25aec75c3c14ad 100644
--- a/mlir/test/lib/Dialect/Linalg/TestLinalgTransforms.cpp
+++ b/mlir/test/lib/Dialect/Linalg/TestLinalgTransforms.cpp
@@ -70,8 +70,8 @@ struct TestLinalgTransforms
       llvm::cl::desc("Test a set of patterns that rewrite a linalg contraction "
                      "in vector.contract form"),
       llvm::cl::init(false)};
-  Option<bool> testGeneralizePadTensor{
-      *this, "test-generalize-pad-tensor",
+  Option<bool> testDecomposePadTensor{
+      *this, "test-decompose-pad-tensor",
       llvm::cl::desc("Test transform pad tensor by copying with generic ops"),
       llvm::cl::init(false)};
   Option<bool> testDecomposeTensorPackOp{
@@ -166,9 +166,9 @@ static void applyLinalgToVectorPatterns(func::FuncOp funcOp) {
   (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
 }
 
-static void applyGeneralizePadTensorPatterns(func::FuncOp funcOp) {
+static void applyDecomposePadPatterns(func::FuncOp funcOp) {
   RewritePatternSet patterns(funcOp.getContext());
-  patterns.add<GeneralizePadOpPattern>(funcOp.getContext());
+  patterns.add<DecomposePadOpPattern>(funcOp.getContext());
   (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
 }
 
@@ -235,8 +235,8 @@ void TestLinalgTransforms::runOnOperation() {
     return applyVectorTransferForwardingPatterns(getOperation());
   if (testGenericToVectorPattern)
     return applyLinalgToVectorPatterns(getOperation());
-  if (testGeneralizePadTensor)
-    return applyGeneralizePadTensorPatterns(getOperation());
+  if (testDecomposePadTensor)
+    return applyDecomposePadPatterns(getOperation());
   if (testDecomposeTensorPackOp)
     return applyDecomposeTensorPackPatterns(getOperation());
   if (testDecomposeTensorUnPackOp)

hanhanW · 2024-11-25T17:53:41Z

mlir/test/Integration/Dialect/Linalg/CPU/pack-dynamic-inner-tile.mlir

-    // NOTE: no tile is transposed, hence no linalg.transpose
-    %func_1 = transform.get_parent_op %tiled_pack_op_p {isolated_from_above} : (!transform.any_op) -> !transform.any_op
-    transform.apply_patterns to %func_1 {
+    // (NOTE: no tile is transposed, hence no linalg.transpose)


Is it because the pack op is decomposed with rank-reduced slices + outer_dims_perm map is empty/identity? Otherwise, I'd expect a transpose op that transposes the inner dimension of the first dimension into inner tiles.

E.g., it should be tensor<?x?x16x1> after expanding the padded tensor, so I'd expect a transpose to bring it to tensor<?x16x?x1>.

%A_pack = tensor.pack %A padding_value(%pad_val : i32) inner_dims_pos = [0, 1] inner_tiles = [%tile_size, 1] into %A_pack_empty : tensor<7x16xi32> -> tensor<?x16x?x1xi32>

In this example, note that no dimensions are transposed:

inner_dims_pos is an identity.

There's no outer_dims_perm (so it's also an identity).

Referring to the original tensor.pack:

We start with tensor<7x16xi32> and tile:

Dimension 7 using %tile_size (which is %c8).

Dimension 16 using 1.

This results in ?x1 as the trailing/inner dimensions in the output tensor.

The remaining dimensions form ?x16 as the outer dimensions in the output tensor:

? corresponds to the tiling along 7.

16 comes from the calculation original_dim / tile_size = 16 / 1 = 16.

Does this make sense? Let me know if anything needs clarification - I want to ensure I'm explaining this correctly 😅.

Yes, I understood this part. There are few ways to decompose pack ops. We can either drop or not drop unit dims during the decomposition. I think I got the answer in the above transform op. We firstly tile outer dims with tile_size=1, and the outer dimensions all have size=1. Then we decompose the ops. In the decomposition, we use patterns that drop outer unit dims, so there are no transpose ops. So I can connect all the pieces now, thanks!

hanhanW

I reviewed the last commit and it looks good to me, thanks!

[mlir][linalg][nfc] Update pack-dynamic-inner-tile.mlir Builds on: * llvm#117329: Extract GeneralizePadOpPattern into a standalone transformation. * llvm#116373: Update pack-dynamic-inner-tile.mlir. This update adds vectorization to the "pack-dynamic-inner-tile.mlir" pipeline. The pipeline first decomposes `tensor.pack` into `tensor.pad` and then into `linalg.fill` (llvm#117329). Next, `linalg.fill` is vectorized, with vector sizes matching the inner tile sizes of the original `tensor.pack`. ••NOTE:** Depends on llvm#117329 - please only review the top commit!

banach-space requested review from ftynse, nicolasvasilache, dcaballe, hanhanW, Groverkss and rengolin as code owners November 25, 2024 09:46

llvmbot added mlir:linalg mlir labels Nov 25, 2024

banach-space changed the title ~~andrzej/tensor pack e2e vec~~ [mlir][linalg][nfc] Update "pack-dynamic-inner-tile.mlir" Nov 25, 2024

banach-space requested review from javedabsar1 and removed request for rengolin, ftynse, nicolasvasilache and Groverkss November 25, 2024 09:47

hanhanW reviewed Nov 25, 2024

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hanhanW approved these changes Nov 25, 2024

View reviewed changes

banach-space force-pushed the andrzej/tensor_pack_e2e_vec branch from d0e7294 to b1aa3ab Compare November 26, 2024 08:14

banach-space merged commit 79f59af into llvm:main Nov 26, 2024
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