[mlir][tensor] Improve tensor.pack simplication pattern. #76606
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We can rewrite the op to tensor.expand_shape if the packing only happens on inner most dimension.
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@llvm/pr-subscribers-mlir Author: Han-Chung Wang (hanhanW) ChangesA tensor.pack op can be rewritten to a tensor.expand_shape op if the packing only happens on inner most dimension. This also formats the lit checks better. Full diff: https://github.com/llvm/llvm-project/pull/76606.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp b/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
index 67651a2e38c82d..e20450c95ffd5f 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
@@ -35,10 +35,20 @@ struct SimplifyPackToExpandShape : public OpRewritePattern<PackOp> {
LogicalResult matchAndRewrite(PackOp packOp,
PatternRewriter &rewriter) const override {
+ if (packOp.getPaddingValue())
+ return rewriter.notifyMatchFailure(packOp, "expects no padding value");
+
+ if (!packOp.getOuterDimsPerm().empty())
+ return rewriter.notifyMatchFailure(packOp, "expects no outer_dims_perm");
+
RankedTensorType sourceType = packOp.getSourceType();
RankedTensorType destType = packOp.getDestType();
- if (sourceType.getRank() != 1 || packOp.getPaddingValue())
- return failure();
+ ArrayRef<int64_t> dimsPos = packOp.getInnerDimsPos();
+ if (dimsPos.size() != 1 || (dimsPos[0] + 1 != sourceType.getRank())) {
+ return rewriter.notifyMatchFailure(
+ packOp, "expects packing at the innermost dimension");
+ }
+
auto reassociation =
getReassociationIndicesForReshape(sourceType, destType);
if (!reassociation)
diff --git a/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir b/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir
index 049076a67bae53..bdfe18acd86c53 100644
--- a/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir
+++ b/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir
@@ -1,9 +1,9 @@
// RUN: mlir-opt -split-input-file -test-tensor-transform-patterns="test-simplify-pack-unpack-patterns" %s | FileCheck %s
-// CHECK: func.func @single_dim_packing(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<256xf32>)
-// CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1]] : tensor<256xf32> into tensor<8x32xf32>
-// CHECK: return %[[EXPANDED]] : tensor<8x32xf32>
+// CHECK-LABEL: func.func @single_dim_packing(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<256xf32>)
+// CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1]] : tensor<256xf32> into tensor<8x32xf32>
+// CHECK: return %[[EXPANDED]] : tensor<8x32xf32>
func.func @single_dim_packing(%arg0: tensor<256xf32>) -> tensor<8x32xf32> {
%empty = tensor.empty() : tensor<8x32xf32>
%0 = tensor.pack %arg0 inner_dims_pos = [0] inner_tiles = [32] into %empty : tensor<256xf32> -> tensor<8x32xf32>
@@ -12,13 +12,47 @@ func.func @single_dim_packing(%arg0: tensor<256xf32>) -> tensor<8x32xf32> {
// -----
-// CHECK: func.func @single_dim_packing_with_padding(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<255xf32>)
-// CHECK-NOT: tensor.expand_shape
-// CHECK: tensor.pack
+// CHECK-LABEL: func.func @single_dim_packing_with_padding(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<255xf32>)
+// CHECK-NOT: tensor.expand_shape
+// CHECK: tensor.pack
func.func @single_dim_packing_with_padding(%arg0: tensor<255xf32>) -> tensor<8x32xf32> {
%empty = tensor.empty() : tensor<8x32xf32>
%cst = arith.constant 0.000000e+00 : f32
%0 = tensor.pack %arg0 padding_value(%cst : f32) inner_dims_pos = [0] inner_tiles = [32] into %empty : tensor<255xf32> -> tensor<8x32xf32>
return %0 : tensor<8x32xf32>
}
+
+// -----
+
+// CHECK-LABEL: func.func @single_last_inner_dim_packing(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<5x256xf32>)
+// CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0], [1, 2]] : tensor<5x256xf32> into tensor<5x8x32xf32>
+// CHECK: return %[[EXPANDED]] : tensor<5x8x32xf32>
+func.func @single_last_inner_dim_packing(%arg0: tensor<5x256xf32>) -> tensor<5x8x32xf32> {
+ %empty = tensor.empty() : tensor<5x8x32xf32>
+ %0 = tensor.pack %arg0 inner_dims_pos = [1] inner_tiles = [32] into %empty : tensor<5x256xf32> -> tensor<5x8x32xf32>
+ return %0 : tensor<5x8x32xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @packing_with_outer_dims_perm(
+// CHECK-NOT: tensor.expand_shape
+// CHECK: tensor.pack
+func.func @packing_with_outer_dims_perm(%arg0: tensor<5x256xf32>) -> tensor<8x5x32xf32> {
+ %empty = tensor.empty() : tensor<8x5x32xf32>
+ %0 = tensor.pack %arg0 outer_dims_perm = [1, 0] inner_dims_pos = [1] inner_tiles = [32] into %empty : tensor<5x256xf32> -> tensor<8x5x32xf32>
+ return %0 : tensor<8x5x32xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @single_first_inner_dim_packing(
+// CHECK-NOT: tensor.expand_shape
+// CHECK: tensor.pack
+func.func @single_first_inner_dim_packing(%arg0: tensor<256x5xf32>) -> tensor<8x5x32xf32> {
+ %empty = tensor.empty() : tensor<8x5x32xf32>
+ %0 = tensor.pack %arg0 inner_dims_pos = [0] inner_tiles = [32] into %empty : tensor<256x5xf32> -> tensor<8x5x32xf32>
+ return %0 : tensor<8x5x32xf32>
+}
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@llvm/pr-subscribers-mlir-tensor Author: Han-Chung Wang (hanhanW) ChangesA tensor.pack op can be rewritten to a tensor.expand_shape op if the packing only happens on inner most dimension. This also formats the lit checks better. Full diff: https://github.com/llvm/llvm-project/pull/76606.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp b/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
index 67651a2e38c82d..e20450c95ffd5f 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
@@ -35,10 +35,20 @@ struct SimplifyPackToExpandShape : public OpRewritePattern<PackOp> {
LogicalResult matchAndRewrite(PackOp packOp,
PatternRewriter &rewriter) const override {
+ if (packOp.getPaddingValue())
+ return rewriter.notifyMatchFailure(packOp, "expects no padding value");
+
+ if (!packOp.getOuterDimsPerm().empty())
+ return rewriter.notifyMatchFailure(packOp, "expects no outer_dims_perm");
+
RankedTensorType sourceType = packOp.getSourceType();
RankedTensorType destType = packOp.getDestType();
- if (sourceType.getRank() != 1 || packOp.getPaddingValue())
- return failure();
+ ArrayRef<int64_t> dimsPos = packOp.getInnerDimsPos();
+ if (dimsPos.size() != 1 || (dimsPos[0] + 1 != sourceType.getRank())) {
+ return rewriter.notifyMatchFailure(
+ packOp, "expects packing at the innermost dimension");
+ }
+
auto reassociation =
getReassociationIndicesForReshape(sourceType, destType);
if (!reassociation)
diff --git a/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir b/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir
index 049076a67bae53..bdfe18acd86c53 100644
--- a/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir
+++ b/mlir/test/Dialect/Tensor/simplify-pack-unpack.mlir
@@ -1,9 +1,9 @@
// RUN: mlir-opt -split-input-file -test-tensor-transform-patterns="test-simplify-pack-unpack-patterns" %s | FileCheck %s
-// CHECK: func.func @single_dim_packing(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<256xf32>)
-// CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1]] : tensor<256xf32> into tensor<8x32xf32>
-// CHECK: return %[[EXPANDED]] : tensor<8x32xf32>
+// CHECK-LABEL: func.func @single_dim_packing(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<256xf32>)
+// CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1]] : tensor<256xf32> into tensor<8x32xf32>
+// CHECK: return %[[EXPANDED]] : tensor<8x32xf32>
func.func @single_dim_packing(%arg0: tensor<256xf32>) -> tensor<8x32xf32> {
%empty = tensor.empty() : tensor<8x32xf32>
%0 = tensor.pack %arg0 inner_dims_pos = [0] inner_tiles = [32] into %empty : tensor<256xf32> -> tensor<8x32xf32>
@@ -12,13 +12,47 @@ func.func @single_dim_packing(%arg0: tensor<256xf32>) -> tensor<8x32xf32> {
// -----
-// CHECK: func.func @single_dim_packing_with_padding(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<255xf32>)
-// CHECK-NOT: tensor.expand_shape
-// CHECK: tensor.pack
+// CHECK-LABEL: func.func @single_dim_packing_with_padding(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<255xf32>)
+// CHECK-NOT: tensor.expand_shape
+// CHECK: tensor.pack
func.func @single_dim_packing_with_padding(%arg0: tensor<255xf32>) -> tensor<8x32xf32> {
%empty = tensor.empty() : tensor<8x32xf32>
%cst = arith.constant 0.000000e+00 : f32
%0 = tensor.pack %arg0 padding_value(%cst : f32) inner_dims_pos = [0] inner_tiles = [32] into %empty : tensor<255xf32> -> tensor<8x32xf32>
return %0 : tensor<8x32xf32>
}
+
+// -----
+
+// CHECK-LABEL: func.func @single_last_inner_dim_packing(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<5x256xf32>)
+// CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0], [1, 2]] : tensor<5x256xf32> into tensor<5x8x32xf32>
+// CHECK: return %[[EXPANDED]] : tensor<5x8x32xf32>
+func.func @single_last_inner_dim_packing(%arg0: tensor<5x256xf32>) -> tensor<5x8x32xf32> {
+ %empty = tensor.empty() : tensor<5x8x32xf32>
+ %0 = tensor.pack %arg0 inner_dims_pos = [1] inner_tiles = [32] into %empty : tensor<5x256xf32> -> tensor<5x8x32xf32>
+ return %0 : tensor<5x8x32xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @packing_with_outer_dims_perm(
+// CHECK-NOT: tensor.expand_shape
+// CHECK: tensor.pack
+func.func @packing_with_outer_dims_perm(%arg0: tensor<5x256xf32>) -> tensor<8x5x32xf32> {
+ %empty = tensor.empty() : tensor<8x5x32xf32>
+ %0 = tensor.pack %arg0 outer_dims_perm = [1, 0] inner_dims_pos = [1] inner_tiles = [32] into %empty : tensor<5x256xf32> -> tensor<8x5x32xf32>
+ return %0 : tensor<8x5x32xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @single_first_inner_dim_packing(
+// CHECK-NOT: tensor.expand_shape
+// CHECK: tensor.pack
+func.func @single_first_inner_dim_packing(%arg0: tensor<256x5xf32>) -> tensor<8x5x32xf32> {
+ %empty = tensor.empty() : tensor<8x5x32xf32>
+ %0 = tensor.pack %arg0 inner_dims_pos = [0] inner_tiles = [32] into %empty : tensor<256x5xf32> -> tensor<8x5x32xf32>
+ return %0 : tensor<8x5x32xf32>
+}
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chelini
approved these changes
Jan 2, 2024
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A tensor.pack op can be rewritten to a tensor.expand_shape op if the packing only happens on inner most dimension.
This also formats the lit checks better.