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[webgpu] Fix BatchNormalization ShapeInferenceError for 2D inputs #26659

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Merged
guschmue merged 1 commit into from
Dec 1, 2025
Merged

[webgpu] Fix BatchNormalization ShapeInferenceError for 2D inputs #26659

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7 changes: 4 additions & 3 deletions onnxruntime/core/graph/contrib_ops/nhwc_inference_context.h
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Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,8 @@ class NhwcInferenceContext : public ONNX_NAMESPACE::InferenceContext {
const int rank = nchw_shape.dim_size();
// N and C dims are required. Some operators like AveragePool allow 1D input
if (rank < 3) {
fail_shape_inference("Output tensor must have at least 3 dimensions");
*nhwc_tp.mutable_tensor_type()->mutable_shape() = nchw_shape;
return;
}

// Convert output shape from N, C, H {, W, ...} to N, H {, W, ...}, C.
Expand All @@ -105,8 +106,8 @@ class NhwcInferenceContext : public ONNX_NAMESPACE::InferenceContext {
const int rank = nhwc_shape.dim_size();
// N and C dims are required. Some operators like AveragePool allow 1D input.
if (rank < 3) {
fail_shape_inference(
"Tensor must have at least 3 dimensions to convert between channels first and channels last.");
*nchw_tp.mutable_tensor_type()->mutable_shape() = nhwc_shape;
return;
}

// Convert input shape from {N, H, W, ..., C} to {N, C, H, W, ...}.
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