\text{in_channels} , iT , iH , iW)
  * **weight** -- filters of shape (\text{out\_channels} ,
    \frac{\text{in\_channels}}{\text{groups}} , kT , kH , kW)

  * **bias** -- optional bias tensor of shape
    (\text{out\_channels}). Default: None

  * **stride** -- the stride of the convolving kernel. Can be a
    single number or a tuple *(sT, sH, sW)*. Default: 1

  * **padding** --

    implicit paddings on both sides of the input. Can be a string
    {'valid', 'same'}, single number or a tuple *(padT, padH,
    padW)*. Default: 0 "padding='valid'" is the same as no
    padding. "padding='same'" pads the input so the output has the
    same shape as the input. However, this mode doesn't support
    any stride values other than 1.

    Warning:

      For "padding='same'", if the "weight" is even-length and
      "dilation" is odd in any dimension, a full "pad()" operation
      may be needed internally. Lowering performance.
