operation deterministic (potentially at a performance cost) by
     setting "torch.backends.cudnn.deterministic = True". Please see
     the notes on Reproducibility for background.
Parameters:
      * in_channels (int) -- Number of channels in the input
        image
  * **out_channels** (*int*) -- Number of channels produced by the
    convolution

  * **kernel_size** (*int** or **tuple*) -- Size of the convolving
    kernel

  * **stride** (*int** or **tuple**, **optional*) -- Stride of the
    convolution. Default: 1

  * **padding** (*int** or **tuple**, **optional*) -- "dilation *
    (kernel_size - 1) - padding" zero-padding will be added to
    both sides of the input. Default: 0

  * **output_padding** (*int** or **tuple**, **optional*) --
    Additional size added to one side of the output shape.
    Default: 0

  * **groups** (*int**, **optional*) -- Number of blocked
