class_docstr: BatchNorm2d where the batch statistics and the affine parameters are fixed
  
  Args:
      num_features (int): Number of features ``C`` from an expected input of size ``(N, C, H, W)``
      eps (float): a value added to the denominator for numerical stability. Default: 1e-5
code: def __repr__(self) -> str:
      return f"{self.__class__.__name__}({self.weight.shape[0]}, eps={self.eps})"
  
imports: import warnings
  from typing import Callable, List, Optional, Sequence, Tuple, Union
  import torch
  from torch import Tensor
  from ..utils import _log_api_usage_once, _make_ntuple
label_desc: Use image node_id 4 for calling the FrozenBatchNorm2d obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str