Conv1d
class torch.ao.nn.quantized.Conv1d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros', device=None, dtype=None)
Applies a 1D convolution over a quantized input signal composed of
   several quantized input planes.
For details on input arguments, parameters, and implementation see
   "Conv1d".
Note:
 Only *zeros* is supported for the "padding_mode" argument.

Note:
 Only *torch.quint8* is supported for the input data type.

Variables:
      * weight (Tensor) -- packed tensor derived from the
        learnable weight parameter.
  * **scale** (*Tensor*) -- scalar for the output scale

  * **zero_point** (*Tensor*) -- scalar for the output zero point

See "Conv1d" for other attributes.
Examples:
  >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2)
  >>> input = torch.randn(20, 16, 100)
  >>> # quantize input to quint8
