[CPU/CUDA] Add bias input validations for ConvTranspose

onnxruntime/core/providers/cpu/nn/conv_transpose_attributes.h

@@ -99,6 +99,18 @@ struct ConvTransposeAttributes : public ConvAttributes {
                              " group: ", group);
     }
 
+    // Bias shape validation (It should be a 1D tensor with size M)
+    // See https://github.com/microsoft/onnxruntime/issues/26144
+    if (B != nullptr) {
+      if (B->Shape().NumDimensions() != 1 || B->Shape()[0] != num_output_channels) {
+        return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT,
+                               "Bias shape is not compatible with number of output channels."
+                               "It should be a 1-D tensor with size num_output_channels(M).",
+                               " Bias: ", B->Shape().ToString().c_str(),
+                               " num_output_channels: ", num_output_channels);
+      }
+    }
+
     TensorShapeVector kernel_shape;
     ORT_RETURN_IF_ERROR(ComputeKernelShape(F_Shape, kernel_shape, is_nhwc));
 

onnxruntime/test/providers/cpu/nn/conv_transpose_op_test.cc

@@ -529,6 +529,38 @@ TEST(ConvTransposeTest, ConvTranspose_InvalidKernelShape) {
                        kDmlExecutionProvider});  // TODO: Unskip when fixed #41968513
 }
 
+TEST(ConvTransposeTest, ConvTranspose_InvalidBiasShape) {
+  ConvTransposeOpAttributes attrs = {
+      vector<int64_t>{1, 5},         // kernel_shape
+      {},                            // output_padding
+      vector<int64_t>{2, 1, 1, 14},  // output_shape
+      vector<int64_t>{0, 0, 0, 0},   // pads
+      vector<int64_t>{1, 1},         // strides
+      vector<int64_t>{1, 1},         // dilations
+      1,                             // group
+      "NOTSET"                       // auto_pad
+  };
+  vector<float> X = {0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
+                     10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f};
+  vector<int64_t> X_shape = {2, 1, 1, 10};
+  vector<float> W = {1.0f, 2.0f, 3.0f, 2.0f, 1.0f};
+  vector<int64_t> W_shape = {1, 1, 1, 5};
+  vector<float> B = {1.0f, 2.0f};  // invalid bias shape, should be {1}
+  vector<int64_t> B_shape = {2};   // invalid bias shape, should be {1}
+  vector<int64_t> Y_shape = {2, 1, 1, 14};
+  vector<float> expected_vals = {1.0f, 2.0f, 5.0f, 11.0f, 19.0f, 28.0f, 37.0f, 46.0f, 55.0f, 64.0f, 63.0f, 51.0f, 27.0f, 10.0f,
+                                 11.0f, 32.0f, 65.0f, 91.0f, 109.0f, 118.0f, 127.0f, 136.0f, 145.0f, 154.0f, 143.0f, 111.0f, 57.0f, 20.0f};
+  TestConvTransposeOp(attrs, {X, W, B}, {X_shape, W_shape, B_shape}, expected_vals, Y_shape,
+                      OpTester::ExpectResult::kExpectFailure,
+                      // Just ensure that it starts with the expected string.
+                      "Bias shape is not compatible with number of output channels. "
+                      "It should be a 1-D tensor with size num_output_channels(M).",
+                      // The EP exclusions are along the same lines as the above test which
+                      // also tests for invalid shapes.
+                      {kTensorrtExecutionProvider, kQnnExecutionProvider,
+                       kDmlExecutionProvider});
+}
+
 TEST(ConvTransposeTest, ConvTranspose_onnx) {
   ConvTransposeOpAttributes attrs = {
       vector<int64_t>{3, 3},        // kernel_shape