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 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>