class_docstr: Element-wise affine transform like no-population stats BatchNorm alternative.
  
  Args:
      channels (int): Number of input tensor channels.
code: def __init__(self, channels):
      super().__init__()
      self.translation = nn.Parameter(torch.zeros(channels, 1))
      self.log_scale = nn.Parameter(torch.zeros(channels, 1))
  
imports: import math
  import torch
  from torch import nn
  from torch.nn import functional
  from TTS.tts.layers.generic.normalization import LayerNorm2
  from TTS.tts.layers.vits.transforms import piecewise_rational_quadratic_transform
label_desc: Use image node_id 1 to create a new ElementwiseAffine object from inherited base classes: nn with example: obj = ElementwiseAffine(channels)