can try to make the operation deterministic (potentially at a
     performance cost) by setting "torch.backends.cudnn.deterministic
     = True". See Reproducibility for more information.
Note:
 "padding='valid'" is the same as no padding. "padding='same'"
 pads the input so the output has the shape as the input. However,
 this mode doesn't support any stride values other than 1.

Note:
 This module supports complex data types i.e. "complex32,
 complex64, complex128".

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**, **tuple** or **str**, **optional*) --
    Padding added to all six sides of the input. Default: 0
