code: def __init__(
      self,
      num_features,
      eps=1e-5,
      momentum=0.1,
      affine=True,
      track_running_stats=False,
  ):
      super(ComplexBatchNorm, self).__init__()
      self.num_features = num_features
      self.eps = eps
      self.momentum = momentum
      self.affine = affine
      self.track_running_stats = track_running_stats
      if self.affine:
          self.Wrr = torch.nn.Parameter(torch.Tensor(num_features))
          self.Wri = torch.nn.Parameter(torch.Tensor(num_features))
          self.Wii = torch.nn.Parameter(torch.Tensor(num_features))
          self.Br = torch.nn.Parameter(torch.Tensor(num_features))
          self.Bi = torch.nn.Parameter(torch.Tensor(num_features))
      else:
          self.register_parameter("Wrr", None)
          self.register_parameter("Wri", None)
          self.register_parameter("Wii", None)
          self.register_parameter("Br", None)
          self.register_parameter("Bi", None)
      if self.track_running_stats:
          self.register_buffer("RMr", torch.zeros(num_features))
          self.register_buffer("RMi", torch.zeros(num_features))
          self.register_buffer("RVrr", torch.ones(num_features))
          self.register_buffer("RVri", torch.zeros(num_features))
          self.register_buffer("RVii", torch.ones(num_features))
          self.register_buffer(
              "num_batches_tracked", torch.tensor(0, dtype=torch.long)
          )
      else:
          self.register_parameter("RMr", None)
          self.register_parameter("RMi", None)
          self.register_parameter("RVrr", None)
          self.register_parameter("RVri", None)
          self.register_parameter("RVii", None)
          self.register_parameter("num_batches_tracked", None)
      self.reset_parameters()
  
imports: import functools
  from functools import partial
  import numpy
  import torch
  from torch import Tensor, nn
  from torch.nn.modules.batchnorm import _BatchNorm
label_desc: Use image node_id 1 to create a new ComplexBatchNorm object from inherited base classes: torch.nn with example: obj = ComplexBatchNorm(num_features, eps, momentum, affine, track_running_stats)