channels and producing half the output channels, and both
          subsequently concatenated.
    * At groups= "in_channels", each input channel is convolved
      with its own set of filters (of size
      \frac{\text{out\_channels}}{\text{in\_channels}}).

The parameters "kernel_size", "stride", "padding", "output_padding"
   can either be:
  * a single "int" -- in which case the same value is used for the
    depth, height and width dimensions

  * a "tuple" of three ints -- in which case, the first *int* is
    used for the depth dimension, the second *int* for the height
    dimension and the third *int* for the width dimension

Note:
 The "padding" argument effectively adds "dilation * (kernel_size
 - 1) - padding" amount of zero padding to both sizes of the
 input. This is set so that when a "Conv3d" and a
 "ConvTranspose3d" are initialized with same parameters, they are
