code: def __init__(
      self, num_features, apply_act=True, momentum=0.1, eps=1e-5, **_
  ):
      super().__init__()
      self.apply_act = apply_act  # apply activation (non-linearity)
      self.momentum = momentum
      self.eps = eps
      self.weight = nn.Parameter(torch.ones(num_features))
      self.bias = nn.Parameter(torch.zeros(num_features))
      self.register_buffer("running_var", torch.ones(num_features))
      self.reset_parameters()
  
imports: from typing import Sequence, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from .create_act import create_act_layer
  from .trace_utils import _assert
label_desc: Use image node_id 1 to create a new EvoNorm2dB2 object from inherited base classes: nn with example: obj = EvoNorm2dB2(num_features, apply_act, momentum, eps)