cudnn only accepts contiguous inputs

mlx/backend/cuda/conv.cpp

@@ -1,6 +1,7 @@
 // Copyright © 2025 Apple Inc.
 
 #include "mlx/backend/cuda/device.h"
+#include "mlx/backend/gpu/copy.h"
 #include "mlx/dtype_utils.h"
 #include "mlx/primitives.h"
 
@@ -168,12 +169,24 @@ auto nhwc_to_nchw(const array& in) {
 void Convolution::eval_gpu(const std::vector<array>& inputs, array& out) {
   nvtx3::scoped_range r("Convolution::eval_gpu");
   assert(inputs.size() == 2);
-  const array& in = inputs[0];
-  const array& wt = inputs[1];
+  array in = inputs[0];
+  array wt = inputs[1];
   out.set_data(allocator::malloc(out.nbytes()));
 
   auto& s = stream();
   auto& encoder = cu::get_command_encoder(s);
+
+  // While cuDNN supports passing arbitrary strides, it would fail to build a
+  // plan with non-contiguous input.
+  if (!in.flags().row_contiguous) {
+    in = contiguous_copy_gpu(in, s);
+    encoder.add_temporary(in);
+  }
+  if (!wt.flags().row_contiguous) {
+    wt = contiguous_copy_gpu(wt, s);
+    encoder.add_temporary(wt);
+  }
+
   encoder.set_input_array(in);
   encoder.set_input_array(wt);
   encoder.set_output_array(out);

python/tests/cuda_skip.py

@@ -16,12 +16,10 @@ cuda_skip = {
     # Convolutions NYI
     "TestConv.test_1d_conv_with_2d",
     "TestConv.test_asymmetric_padding",
-    "TestConv.test_conv2d_unaligned_channels",
     "TestConv.test_conv_1d_groups_flipped",
     "TestConv.test_conv_general_flip_grad",
     "TestConv.test_conv_groups_grad",
     "TestConv.test_numpy_conv",
-    "TestConv.test_repeated_conv",
     "TestConv.test_torch_conv_1D",
     "TestConv.test_torch_conv_1D_grad",
     "TestConv.test_torch_conv_2D",
@@ -39,7 +37,6 @@ cuda_skip = {
     "TestConvTranspose.test_torch_conv_transpose_3D",
     "TestConvTranspose.test_torch_conv_transpose_3D_grad",
     "TestConvTranspose.test_torch_conv_transpose_3d_output_padding",
-    "TestExportImport.test_export_conv",
     "TestLayers.test_conv1d",
     "TestLayers.test_conv2d",
     "TestVmap.test_vmap_conv",