[Mlir-commits] [mlir] [mlir][linalg] Add pure tensor check for `winogradConv2DHelper` (PR #142299)

[llvmlistbot at llvm.org]

llvmbot wrote:


<!--LLVM PR SUMMARY COMMENT-->

@llvm/pr-subscribers-mlir

Author: Longsheng Mou (CoTinker)

<details>
<summary>Changes</summary>

This PR adds pure tensor semantics check for `winogradConv2DHelper` to prevent a crash. Fixes #<!-- -->141566.

---
Full diff: https://github.com/llvm/llvm-project/pull/142299.diff


2 Files Affected:

- (modified) mlir/lib/Dialect/Linalg/Transforms/WinogradConv2D.cpp (+4) 
- (modified) mlir/test/Dialect/Linalg/transform-winograd-conv2d.mlir (+16) 


``````````diff
diff --git a/mlir/lib/Dialect/Linalg/Transforms/WinogradConv2D.cpp b/mlir/lib/Dialect/Linalg/Transforms/WinogradConv2D.cpp
index c6ebd3a53d981..e4221d4748415 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/WinogradConv2D.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/WinogradConv2D.cpp
@@ -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];
diff --git a/mlir/test/Dialect/Linalg/transform-winograd-conv2d.mlir b/mlir/test/Dialect/Linalg/transform-winograd-conv2d.mlir
index c10e0ccebfd7c..1de861e653005 100644
--- a/mlir/test/Dialect/Linalg/transform-winograd-conv2d.mlir
+++ b/mlir/test/Dialect/Linalg/transform-winograd-conv2d.mlir
@@ -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>

``````````

</details>


https://github.com/llvm/llvm-project/pull/142299