code: def __init__(self, channels):
      super().__init__()
      self.channels = channels
      self.m = nn.Parameter(torch.zeros(channels, 1))
      self.logs = nn.Parameter(torch.zeros(channels, 1))
  
imports: import torch
  from torch import nn
  from torch.nn import Conv1d
  from torch.nn import functional
  from torch.nn.utils.parametrizations import weight_norm
  from torch.nn.utils.parametrize import remove_parametrizations
  import TTS.vc.modules.freevc.commons
  from TTS.vc.modules.freevc.commons import get_padding, init_weights
label_desc: Use image node_id 1 to create a new ElementwiseAffine object from inherited base classes: nn with example: obj = ElementwiseAffine(channels)