class_docstr: BatchNorm2d where the batch statistics and the affine parameters are fixed
code: def get_scale_bias(self, nhwc):
      # type: (bool) -> List[torch.Tensor]
      scale = self.weight * self.running_var.rsqrt()
      bias = self.bias - self.running_mean * scale
      if nhwc:
          scale = scale.reshape(1, 1, 1, -1)
          bias = bias.reshape(1, 1, 1, -1)
      else:
          scale = scale.reshape(1, -1, 1, 1)
          bias = bias.reshape(1, -1, 1, 1)
      return scale, bias
  
imports: import functools
  import torch
  import torch.distributed
  from torch import nn
  from apex import check_cudnn_version_and_warn
  import fast_bottleneck
  import nccl_p2p_cuda
label_desc: Use image node_id 2 for calling the FrozenBatchNorm2d obj's underlying member method code with example usage: obj.get_scale_bias(nhwc) and returns: scale,  bias