[Mlir-commits] [mlir] 2a25200 - [mlir][tensor] Restrict the verifier for tensor.pack/tensor.unpack (#113108)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Oct 22 20:11:09 PDT 2024
Author: Andrzej Warzyński
Date: 2024-10-22T20:11:05-07:00
New Revision: 2a2520082882d857b22f16e9efa8f794d328f3ee
URL: https://github.com/llvm/llvm-project/commit/2a2520082882d857b22f16e9efa8f794d328f3ee
DIFF: https://github.com/llvm/llvm-project/commit/2a2520082882d857b22f16e9efa8f794d328f3ee.diff
LOG: [mlir][tensor] Restrict the verifier for tensor.pack/tensor.unpack (#113108)
Restricts the verifier for tensor.pack and tensor.unpack Ops so that the
following is no longer allowed:
```mlir
%c8 = arith.constant 8 : index
%0 = tensor.pack %input inner_dims_pos = [0, 1] inner_tiles = [8, %c8] into %output : tensor<?x?xf32> -> tensor<?x?x8x8xf32>
```
Specifically, in line with other Tensor Ops, require:
* a dynamic dimensions for each (dynamic) SSA value,
* a static dimension for each static size (attribute).
In the example above, a static dimension (8) is mixed with a dynamic
size (%c8).
Note that this is mostly deleting existing code - that's because this
change simplifies the logic in verifier.
For more context:
* https://discourse.llvm.org/t/tensor-ops-with-dynamic-sizes-which-behaviour-is-more-correct
Added:
Modified:
mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
mlir/test/Dialect/Linalg/transform-lower-pack.mlir
mlir/test/Dialect/Tensor/fold-empty-op.mlir
mlir/test/Dialect/Tensor/invalid.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
index 4d6c5965c4fcc3..603e86ca3d7668 100644
--- a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
+++ b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
@@ -3865,22 +3865,14 @@ static LogicalResult commonVerifierPackAndUnPackOp(OpTy packOrUnPack) {
llvm::zip(packedType.getShape().take_back(mixedTiles.size()),
mixedTiles),
[](std::tuple<int64_t, OpFoldResult> it) {
- std::optional<int64_t> constTileSize =
- getConstantIntValue(std::get<1>(it));
int64_t shape = std::get<0>(it);
- if (!constTileSize) {
- // If specified tile size is dynamic, output shape should
- // be dynamic too.
- return ShapedType::isDynamic(shape);
+ if (Attribute attr =
+ llvm::dyn_cast_if_present<Attribute>(std::get<1>(it))) {
+ IntegerAttr intAttr = dyn_cast_or_null<IntegerAttr>(attr);
+ int64_t staticTileSize = intAttr.getValue().getSExtValue();
+ return shape == staticTileSize;
}
- if (ShapedType::isDynamic(shape)) {
- // For the shape being dynamic when tile size is
- // specified, return true. In canonical form a constant
- // tile size should lead to constant shape of the tiled
- // dimension, but not needed for verification.
- return true;
- }
- return shape == constTileSize.value();
+ return ShapedType::isDynamic(shape);
})) {
return op->emitError("mismatch in inner tile sizes specified and shaped of "
"tiled dimension in the packed type");
diff --git a/mlir/test/Dialect/Linalg/transform-lower-pack.mlir b/mlir/test/Dialect/Linalg/transform-lower-pack.mlir
index 48bf1c151de8f5..7aadf190695630 100644
--- a/mlir/test/Dialect/Linalg/transform-lower-pack.mlir
+++ b/mlir/test/Dialect/Linalg/transform-lower-pack.mlir
@@ -586,7 +586,7 @@ module attributes {transform.with_named_sequence} {
// Check that we can lower unpack "as unpad" with dynamic dims.
// CHECK-LABEL: func.func @unpack_as_pad_dynamic(
-// CHECK-SAME: %[[ARG0:.*]]: tensor<1x1x1x1x?x?x?x?xf32>, %[[ARG1:.*]]: tensor<?x?x?x?xf32>
+// CHECK-SAME: %[[ARG0:.*]]: tensor<1x1x1x1x136x64x16x16xf32>, %[[ARG1:.*]]: tensor<?x?x?x?xf32>
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
@@ -602,10 +602,10 @@ module attributes {transform.with_named_sequence} {
// CHECK-SAME: [1, 1, 1, 1, %[[DIM0]], %[[DIM1]], %[[DIM2]], %[[DIM3]]]
// strides multiplers.
// CHECK-SAME: [1, 1, 1, 1, 1, 1, 1, 1]
-// CHECK-SAME: : tensor<1x1x1x1x?x?x?x?xf32> to tensor<?x?x?x?xf32>
-func.func @unpack_as_pad_dynamic(%arg0: tensor<1x1x1x1x?x?x?x?xf32>, %arg1: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
+// CHECK-SAME: : tensor<1x1x1x1x136x64x16x16xf32> to tensor<?x?x?x?xf32>
+func.func @unpack_as_pad_dynamic(%arg0: tensor<1x1x1x1x136x64x16x16xf32>, %arg1: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
%pack = tensor.unpack %arg0 inner_dims_pos = [0, 1, 2, 3] inner_tiles = [136, 64, 16, 16] into %arg1
- : tensor<1x1x1x1x?x?x?x?xf32> -> tensor<?x?x?x?xf32>
+ : tensor<1x1x1x1x136x64x16x16xf32> -> tensor<?x?x?x?xf32>
return %pack : tensor<?x?x?x?xf32>
}
diff --git a/mlir/test/Dialect/Tensor/fold-empty-op.mlir b/mlir/test/Dialect/Tensor/fold-empty-op.mlir
index 5beb8c250aa105..65ceb4ff3e3df4 100644
--- a/mlir/test/Dialect/Tensor/fold-empty-op.mlir
+++ b/mlir/test/Dialect/Tensor/fold-empty-op.mlir
@@ -77,20 +77,20 @@ func.func @pack_empty(%arg0: tensor<8x8x32x32xf32>) -> tensor<8x8x32x32xf32> {
// CHECK-NOT: tensor.pack
// CHECK: return %[[T]] : tensor<8x8x32x32xf32>
-func.func @pack_empty_dynamic(%arg0: tensor<?x?x?x?xf32>, %dim0: index, %dim1: index) -> tensor<?x?x?x?xf32> {
+func.func @pack_empty_dynamic(%arg0: tensor<?x?x32x32xf32>, %dim0: index, %dim1: index) -> tensor<?x?x32x32xf32> {
%empty_unpacked = tensor.empty(%dim0, %dim1) : tensor<?x?xf32>
%packed = tensor.pack %empty_unpacked
inner_dims_pos = [0, 1] inner_tiles = [32, 32]
- into %arg0 : tensor<?x?xf32> -> tensor<?x?x?x?xf32>
- return %packed : tensor<?x?x?x?xf32>
+ into %arg0 : tensor<?x?xf32> -> tensor<?x?x32x32xf32>
+ return %packed : tensor<?x?x32x32xf32>
}
// CHECK-LABEL: func.func @pack_empty_dynamic(
-// CHECK-SAME: %[[T:.+]]: tensor<?x?x?x?xf32>,
+// CHECK-SAME: %[[T:.+]]: tensor<?x?x32x32xf32>,
// CHECK-SAME: %[[DIM0:[a-zA-Z0-9_]+]]: index,
// CHECK-SAME: %[[DIM1:[a-zA-Z0-9_]+]]: index
// CHECK-NOT: tensor.pack
-// CHECK: return %[[T]] : tensor<?x?x?x?xf32>
+// CHECK: return %[[T]] : tensor<?x?x32x32xf32>
func.func @unpack_empty(%arg0: tensor<256x256xf32>) -> tensor<256x256xf32> {
%empty_packed = tensor.empty() : tensor<8x8x32x32xf32>
@@ -105,20 +105,18 @@ func.func @unpack_empty(%arg0: tensor<256x256xf32>) -> tensor<256x256xf32> {
// CHECK-NOT: tensor.unpack
// CHECK: return %[[T]] : tensor<256x256xf32>
-func.func @unpack_empty_dynamic(%arg0: tensor<?x?xf32>, %dim0: index, %dim1: index, %dim2: index, %dim3: index) -> tensor<?x?xf32> {
- %empty_packed = tensor.empty(%dim0, %dim1, %dim2, %dim3) : tensor<?x?x?x?xf32>
+func.func @unpack_empty_dynamic(%arg0: tensor<?x?xf32>, %dim0: index, %dim1: index) -> tensor<?x?xf32> {
+ %empty_packed = tensor.empty(%dim0, %dim1) : tensor<?x?x32x32xf32>
%unpacked = tensor.unpack %empty_packed
inner_dims_pos = [0, 1] inner_tiles = [32, 32]
- into %arg0 : tensor<?x?x?x?xf32> -> tensor<?x?xf32>
+ into %arg0 : tensor<?x?x32x32xf32> -> tensor<?x?xf32>
return %unpacked : tensor<?x?xf32>
}
// CHECK-LABEL: func.func @unpack_empty_dynamic(
// CHECK-SAME: %[[T:.+]]: tensor<?x?xf32>,
// CHECK-SAME: %[[DIM0:[a-zA-Z0-9_]+]]: index,
-// CHECK-SAME: %[[DIM1:[a-zA-Z0-9_]+]]: index,
-// CHECK-SAME: %[[DIM2:[a-zA-Z0-9_]+]]: index,
-// CHECK-SAME: %[[DIM3:[a-zA-Z0-9_]+]]: index
+// CHECK-SAME: %[[DIM1:[a-zA-Z0-9_]+]]: index
// CHECK-NOT: tensor.unpack
// CHECK: return %[[T]] : tensor<?x?xf32>
diff --git a/mlir/test/Dialect/Tensor/invalid.mlir b/mlir/test/Dialect/Tensor/invalid.mlir
index 921d7f9f1fefc3..be470ce2af9b31 100644
--- a/mlir/test/Dialect/Tensor/invalid.mlir
+++ b/mlir/test/Dialect/Tensor/invalid.mlir
@@ -755,9 +755,47 @@ func.func @pack_mismatch_inner_tile_size_and_output_shape(
// -----
+func.func @pack_dynamic_inner_tile_size_and_static_output_shape(
+ %input : tensor<?x?xf32>, %output : tensor<?x?x8x8xf32>) -> tensor<?x?x8x8xf32> {
+ %c8 = arith.constant 8 : index
+ // expected-error at +1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}}
+ %0 = tensor.pack %input inner_dims_pos = [0, 1] inner_tiles = [8, %c8] into %output : tensor<?x?xf32> -> tensor<?x?x8x8xf32>
+ return %0 : tensor<?x?x8x8xf32>
+}
+
+// -----
+
+func.func @pack_static_inner_tile_size_and_dynamic_output_shape(
+ %input : tensor<?x?xf32>, %output : tensor<?x?x8x?xf32>) -> tensor<?x?x8x?xf32> {
+ // expected-error at +1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}}
+ %0 = tensor.pack %input inner_dims_pos = [0, 1] inner_tiles = [8, 8] into %output : tensor<?x?xf32> -> tensor<?x?x8x?xf32>
+ return %0 : tensor<?x?x8x?xf32>
+}
+
+// -----
+
func.func @unpack_mismatch_inner_tile_size_and_output_shape(
%input : tensor<?x?x8x8xf32>, %output : tensor<?x?xf32>) -> tensor<?x?xf32> {
// expected-error at +1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}}
%0 = tensor.unpack %input inner_dims_pos = [0, 1] inner_tiles = [8, 4] into %output : tensor<?x?x8x8xf32> -> tensor<?x?xf32>
return %0 : tensor<?x?xf32>
}
+
+// -----
+
+func.func @unpack_dynamic_inner_tile_size_and_static_output_shape(
+ %input : tensor<?x?x8x4xf32>, %output : tensor<?x?xf32>) -> tensor<?x?xf32> {
+ %c8 = arith.constant 8 : index
+ // expected-error at +1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}}
+ %0 = tensor.unpack %input inner_dims_pos = [0, 1] inner_tiles = [%c8, 4] into %output : tensor<?x?x8x4xf32> -> tensor<?x?xf32>
+ return %0 : tensor<?x?xf32>
+}
+
+// -----
+
+func.func @unpack_static_inner_tile_size_and_dynamic_output_shape(
+ %input : tensor<?x?x?x4xf32>, %output : tensor<?x?xf32>) -> tensor<?x?xf32> {
+ // expected-error at +1 {{mismatch in inner tile sizes specified and shaped of tiled dimension in the packed type}}
+ %0 = tensor.unpack %input inner_dims_pos = [0, 1] inner_tiles = [8, 4] into %output : tensor<?x?x?x4xf32> -> tensor<?x?xf32>
+ return %0 : tensor<?x?xf32>
+}
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