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linear

class torch.ao.nn.quantized.functional.linear(input, weight, bias=None, scale=None, zero_point=None)[source]

Applies a linear transformation to the incoming quantized data: y=xAT+by = 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)(N, *, in\_features) where * means any number of additional dimensions

  • Weight: (out_features,in_features)(out\_features, in\_features)

  • Bias: (out_features)(out\_features)

  • Output: (N,,out_features)(N, *, out\_features)

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