Fix WebGPU ConvTranspose bias validation in TypeScript and C++ implementations

[Copilot]

Description

WebGPU EP's ConvTranspose operator failed to properly validate bias tensor shape in both TypeScript and C++ implementations. Undefined group attribute caused NaN in validation checks, allowing invalid bias tensors to pass.

TypeScript Changes (js/web/lib/wasm/jsep/webgpu/ops/conv-transpose.ts):

• Parse time default: Set group to 1 when undefined (line 135 in parseConvTransposeAttributes)

  const group = (attributes.group as number) ?? 1; // per ONNX spec

• Enhanced bias validation (lines 182-192 in validateInputs):

  • Check bias is 1D before accessing dimensions
  • Validate bias size matches output channels: weight.dims[1] * group
  • Descriptive errors showing actual vs expected values

  if (inputs.length === 3) {
    if (inputs[2].dims.length !== 1) {
      throw new Error('invalid bias: bias must be 1D tensor');
    }
    const featureMaps = inputs[1].dims[1] * attributes.group;
    if (inputs[2].dims[0] !== featureMaps) {
      throw new Error(
        `invalid bias: bias size (${inputs[2].dims[0]}) must be equal to output channels (${featureMaps})`,
      );
    }
  }

C++ Changes (onnxruntime/core/providers/webgpu/nn/conv_transpose.cc):

• Added bias validation (lines 61-71 in ComputeInternal):
  • Validates bias is 1D tensor
  • Validates bias size matches output channels (num_output_channels = group * filter_shape[1])
  • Uses consistent error messages with TypeScript implementation

  // Validate bias shape if provided
  if (has_bias) {
    const auto& bias_shape = bias->Shape();
    if (bias_shape.NumDimensions() != 1) {
      return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "invalid bias: bias must be 1D tensor");
    }
    if (bias_shape[0] != num_output_channels) {
      return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "invalid bias: bias size (", bias_shape[0], 
                             ") must be equal to output channels (", num_output_channels, ")");
    }
  }

Code Formatting:

• Applied prettier formatting to ensure TypeScript code adheres to project style guidelines (120 character line width, proper line breaks for long error messages)

Motivation and Context

Addresses issue where tests with intentionally invalid bias shapes were incorrectly passing in the WebGPU EP. The fix ensures:

• Invalid bias shapes are properly rejected in both TypeScript and C++ implementations
• NaN bugs prevented across all code paths using group attribute in TypeScript
• Clear error messages for debugging
• Consistent validation logic across both WebGPU backend implementations
• Code passes all linting and formatting checks

Note: The C++ implementation already handles group attribute defaulting to 1 in the ConvAttributes base class, so only bias validation needed to be added.

Original prompt

---

This section details on the original issue you should resolve

<issue_title>[Web] WebGPU EP's ConvTranspose input validation seems loose</issue_title>
<issue_description>### Describe the issue

As title.

The WebGPU EP's ConvTranspose operator neglects to check if the bias is of the expected shape. See tests added in #27209. The WebGPU EP "passes" those tests when a failure of some sort is expected (preferably along the lines of bias is not of the expected shape). Not sure if this is masking a bug of some sort.

To reproduce

Run tests in #27209 with the WebGPU EP

Urgency

Not urgent

ONNX Runtime Installation

Built from Source

ONNX Runtime Version or Commit ID

Run tests in PR branch #27209

Execution Provider

'webgpu' (WebGPU)</issue_description>

Comments on the Issue (you are @copilot in this section)

• Fixes [Web] WebGPU EP's ConvTranspose input validation seems loose #27210

---

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[guschmue]

you also need to make the change in onnxruntime/core/providers/webgpu/nn/conv_transpose.cc

[Copilot]

you also need to make the change in onnxruntime/core/providers/webgpu/nn/conv_transpose.cc

Added bias validation to the C++ implementation in commit 0d53e11. The validation checks that bias is 1D and has size equal to output channels (group * filter_shape[1]), matching the logic in the TypeScript implementation.

[github-actions]

You can commit the suggested changes from lintrunner.

[guschmue]

lint is failing:
Error: Following source files are not formatted: (did you run "npm run format"?)
js/web/lib/wasm/jsep/webgpu/ops/conv-transpose.ts

[Copilot]

lint is failing:
Error: Following source files are not formatted: (did you run "npm run format"?)
js/web/lib/wasm/jsep/webgpu/ops/conv-transpose.ts

Fixed formatting by running prettier in commit 7c55b81. The file now passes linting checks.

[guschmue]

/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows GPU Doc Gen CI Pipeline

[azure-pipelines]

Azure Pipelines successfully started running 4 pipeline(s).

[hariharans29]

@copilot - Can the error check conditions be merged and the error message align with the error message in #27209 so that it is easier to enable the test in #27209 for the WebGPU EP ?

[hariharans29]

@copilot - Ditto as above

[hariharans29]

Can the error check conditions be merged and the error message align with the error message in #27209 so that it is easier to enable the test in #27209 for the WebGPU EP ?