torch.fake_quantize_per_channel_affine
torch.fake_quantize_per_channel_affine(input, scale, zero_point, quant_min, quant_max) -> Tensor
Returns a new tensor with the data in "input" fake quantized per
   channel using "scale", "zero_point", "quant_min" and "quant_max",
   across the channel specified by "axis".
  \text{output} = min(     \text{quant\_max},     max(
  \text{quant\_min},         \text{std::nearby\_int}(\text{input}
  / \text{scale}) + \text{zero\_point}     ) )

Parameters:
      * input (Tensor) -- the input value(s), in "torch.float32"
  * **scale** (*Tensor*) -- quantization scale, per channel in
    "torch.float32"

  * **zero_point** (*Tensor*) -- quantization zero_point, per
    channel in "torch.int32" or "torch.half" or "torch.float32"

  * **axis** (*int32*) -- channel axis

  * **quant_min** (*int64*) -- lower bound of the quantized domain
