Linear
class torch.ao.nn.quantized.dynamic.Linear(in_features, out_features, bias_=True, dtype=torch.qint8)
A dynamic quantized linear module with floating point tensor as
   inputs and outputs. We adopt the same interface as
   torch.nn.Linear, please see
   https://pytorch.org/docs/stable/nn.html#torch.nn.Linear for
   documentation.
Similar to "torch.nn.Linear", attributes will be randomly
   initialized at module creation time and will be overwritten later
Variables:
      * weight (Tensor) -- the non-learnable quantized weights
        of the module which are of shape (\text{out_features},
        \text{in_features}).
  * **bias** (*Tensor*) -- the non-learnable floating point bias
    of the module of shape (\text{out\_features}). If "bias" is
    "True", the values are initialized to zero.

Examples:
  >>> m = nn.quantized.dynamic.Linear(20, 30)
  >>> input = torch.randn(128, 20)
  >>> output = m(input)
  >>> print(output.size())
