linear
class torch.ao.nn.quantized.functional.linear(input, weight, bias=None, scale=None, zero_point=None)
Applies a linear transformation to the incoming quantized data: y =
   xA^T + b. See "Linear"
Note:
 Current implementation packs weights on every call, which has
 penalty on performance. If you want to avoid the overhead, use
 "Linear".

Parameters:
      * input (Tensor) -- Quantized input of type torch.quint8
  * **weight** (*Tensor*) -- Quantized weight of type
    *torch.qint8*

  * **bias** (*Tensor*) -- None or fp32 bias of type *torch.float*

  * **scale** (*double*) -- output scale. If None, derived from
    the input scale

  * **zero_point** (*python:long*) -- output zero point. If None,
    derived from the input zero_point

Return type:
      Tensor
Shape:
      * Input: (N, *, in_features) where *** means any number of
        additional dimensions
  * Weight: (out\_features, in\_features)
