Fix WebGPU Conv auto_pad=SAME_UPPER padding calculation

The WebGPU Conv and ConvTranspose operators were producing incorrect
results when using auto_pad=SAME_UPPER with strides > 1.

Root cause: The head padding values were being unnecessarily recalculated
after InferPadsAndOutputShape() had already computed the correct values.
The recalculation formula could produce incorrect results.

Fix: Simply use pads[0] and pads[1] directly, which already contain the
correct head padding values computed upstream. This matches the behavior
of the TypeScript implementation.

Fixes #26734

Author: ingyukoh

onnxruntime/core/providers/webgpu/nn/conv.cc

@@ -119,10 +119,11 @@ Status Conv<is_channels_last, is_fused>::ComputeInternal(ComputeContext& context
   const auto output_height = output_shape_vector[is_channels_last ? 1 : 2];
   const auto output_width = output_shape_vector[is_channels_last ? 2 : 3];
 
-  uint32_t auto_pad_adjust = conv_attrs_.auto_pad == AutoPadType::SAME_LOWER ? 1 : 0;
-  auto pad0 = conv_attrs_.auto_pad == AutoPadType::NOTSET ? pads[0] : (pads[0] + pads[2] + auto_pad_adjust) / 2;
-  auto pad1 = conv_attrs_.auto_pad == AutoPadType::NOTSET ? pads[1] : (pads[1] + pads[3] + auto_pad_adjust) / 2;
-  std::vector<uint32_t> updated_pads{pad0, pad1};
+  // pads[0] and pads[1] already contain the correct head (beginning) padding values
+  // computed by InferPadsAndOutputShape() which handles auto_pad correctly.
+  // For SAME_UPPER: head gets less padding (pad_needed / 2)
+  // For SAME_LOWER: head gets more padding ((pad_needed + 1) / 2)
+  std::vector<uint32_t> updated_pads{pads[0], pads[1]};
 
   if (CanApplyIm2ColMatMulProgram(context,
                                   is_channels_last,

onnxruntime/core/providers/webgpu/nn/conv_transpose.cc

@@ -87,12 +87,11 @@ Status ConvTranspose<is_channels_last>::ComputeInternal(ComputeContext& context)
     inputs.push_back(bias);
     input_output_shapes.push_back(bias->Shape());
   }
-  uint32_t auto_pad_adjust = conv_transpose_attrs_.auto_pad == AutoPadType::SAME_LOWER ? 1 : 0;
-  auto pad0 = conv_transpose_attrs_.auto_pad == AutoPadType::NOTSET ? pads[0] : (pads[0] + pads[2] + auto_pad_adjust) / 2;
-  auto pad1 = conv_transpose_attrs_.auto_pad == AutoPadType::NOTSET ? pads[1] : (pads[1] + pads[3] + auto_pad_adjust) / 2;
+  // pads[0] and pads[1] already contain the correct head (beginning) padding values
+  // computed by ComputePadsAndOutputShape() which handles auto_pad correctly.
   Tensor* output = context.Output(0, computed_output_shape);
   input_output_shapes.push_back(output_shape);
-  auto program = CreateConvTranspose2DProgram(inputs, {pad0, pad1}, strides, dilations, output, is_channels_last, input_output_shapes, static_cast<uint32_t>(conv_transpose_attrs_.group));
+  auto program = CreateConvTranspose2DProgram(inputs, {pads[0], pads[1]}, strides, dilations, output, is_channels_last, input_output_shapes, static_cast<uint32_t>(conv_transpose_attrs_.group));
   return context.RunProgram(program);
 }