connections from input channels to output channels. Default: 1
  * **bias** (*bool**, **optional*) -- If "True", adds a learnable
    bias to the output. Default: "True"

  * **dilation** (*int** or **tuple**, **optional*) -- Spacing
    between kernel elements. Default: 1

Shape:
      * Input: (N, C_{in}, L_{in}) or (C_{in}, L_{in})
  * Output: (N, C_{out}, L_{out}) or (C_{out}, L_{out}), where

       L_{out} = (L_{in} - 1) \times \text{stride} - 2 \times
       \text{padding} + \text{dilation}           \times
       (\text{kernel\_size} - 1) + \text{output\_padding} + 1

Variables:
      * weight (Tensor) -- the learnable weights of the module
        of shape (\text{in_channels},
        \frac{\text{out_channels}}{\text{groups}},
        \text{kernel_size}). The values of these weights are sampled
        from \mathcal{U}(-\sqrt{k}, \sqrt{k}) where k =
        \frac{groups}{C_\text{out} * \text{kernel_size}}