Comments (1)
dahyun-kang
commented on May 28, 2024
2
Hello, thank you for raising the first issue.
It does not matter since 1 * 1 * 3 * 3 convolution is implemented as 1 * 3 * 3 convolution.
To do so, we first flatten the input spatial dimension of H * W * U * V to HW * U * V and do the 1 * 3 * 3 convolution over the input.
PyTorch does not officially support Conv4d as far as I know, so we needed such trick.
Have a great day! 😃
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