It’s working for me:
conv = nn.Conv2d(1, 64, (3, 6)).cuda().to(memory_format=torch.channels_last)
x = torch.randn(2048, 1, 10, 6).cuda().to(memory_format=torch.channels_last)
out = conv(x)
print(out.shape)
> torch.Size([2048, 64, 8, 1])

As said before, you should not manually permute the tensor, but handle it in the “standard” contiguous layout (channels-first or NCHW).