AvgPool1d
class torch.nn.AvgPool1d(kernel_size, stride=None, padding=0, ceil_mode=False, count_include_pad=True)
Applies a 1D average pooling over an input signal composed of
   several input planes.
In the simplest case, the output value of the layer with input size
   (N, C, L), output (N, C, L_{out}) and "kernel_size" k can be
   precisely described as:
  \text{out}(N_i, C_j, l) = \frac{1}{k} \sum_{m=0}^{k-1}
  \text{input}(N_i, C_j, \text{stride} \times l + m)

If "padding" is non-zero, then the input is implicitly zero-padded
   on both sides for "padding" number of points.
Note:
 When ceil_mode=True, sliding windows are allowed to go off-bounds
 if they start within the left padding or the input. Sliding
 windows that would start in the right padded region are ignored.

The parameters "kernel_size", "stride", "padding" can each be an
   "int" or a one-element tuple.
Parameters:
      * kernel_size (Union[int, Tuple[int]]) --