torch.quantized_batch_norm
torch.quantized_batch_norm(input, weight=None, bias=None, mean, var, eps, output_scale, output_zero_point) -> Tensor
Applies batch normalization on a 4D (NCHW) quantized tensor.
  y = \frac{x - \mathrm{E}[x]}{\sqrt{\mathrm{Var}[x] + \epsilon}}
  * \gamma + \beta

Parameters:
      * input (Tensor) -- quantized tensor
  * **weight** (*Tensor*) -- float tensor that corresponds to the
    gamma, size C

  * **bias** (*Tensor*) -- float tensor that corresponds to the
    beta, size C

  * **mean** (*Tensor*) -- float mean value in batch
    normalization, size C

  * **var** (*Tensor*) -- float tensor for variance, size C

  * **eps** (*float*) -- a value added to the denominator for
    numerical stability.

  * **output_scale** (*float*) -- output quantized tensor scale

  * **output_zero_point** (*int*) -- output quantized tensor
    zero_point

Returns: