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[mlir][linalg] Add pure tensor check for winogradConv2DHelper (#142299)

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This PR adds pure tensor semantics check for `winogradConv2DHelper` to
prevent a crash. Fixes #141566.
This commit is contained in:
Longsheng Mou
2025-06-13 15:49:54 +08:00
committed by GitHub
parent 1f4b172985
commit 02f1f6967a
2 changed files with 20 additions and 0 deletions
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4
mlir/lib/Dialect/Linalg/Transforms/WinogradConv2D.cpp
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@@ -904,6 +904,10 @@ static bool hasAllOneValues(DenseIntElementsAttr attr) {
static FailureOr<Operation *>
winogradConv2DHelper(RewriterBase &rewriter, linalg::Conv2DNhwcFhwcOp convOp,
int64_t m, int64_t r) {
if (!convOp.hasPureTensorSemantics())
return rewriter.notifyMatchFailure(
convOp, "expected pure tensor semantics for linalg.conv_2d_nhwc_fhwc");
Value input = convOp.getInputs()[0];
Value filter = convOp.getInputs()[1];
Value output = convOp.getOutputs()[0];

16
mlir/test/Dialect/Linalg/transform-winograd-conv2d.mlir
View File

@@ -61,6 +61,22 @@ module attributes {transform.with_named_sequence} {
// -----
func.func @conv2d_unsupported_type(%arg0: memref<2x10x10x5xf32>, %arg1: memref<2x3x3x5xf32>, %arg2: memref<2x8x8x2xf32>) {
linalg.conv_2d_nhwc_fhwc {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} ins(%arg0, %arg1 : memref<2x10x10x5xf32>, memref<2x3x3x5xf32>) outs(%arg2 : memref<2x8x8x2xf32>)
return
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match ops{["linalg.conv_2d_nhwc_fhwc"]} in %arg1 : (!transform.any_op) -> !transform.any_op
// expected-error @+1 {{apply Winograd Conv2D failed}}
%1 = transform.structured.winograd_conv2d %0 { m = 4, r = 3 } : (!transform.any_op) -> (!transform.any_op)
transform.yield
}
}
// -----
func.func @conv2d(%arg0: tensor<2x?x?x5xf32>, %arg1: tensor<2x3x3x5xf32>, %arg2: tensor<1xf32>, %arg3: tensor<2x?x?x2xf32>) -> tensor<2x?x?x2xf32> {
%0 = linalg.conv_2d_nhwc_fhwc {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} ins(%arg0, %arg1 : tensor<2x?x?x5xf32>, tensor<2x3x3x5xf32>) outs(%arg3 : tensor<2x?x?x2xf32>) -> tensor<2x?x?x2xf32>
return %0 : tensor<2x?x?x2xf32>