def __init__()

in projects/home/recap/model/feature_transform.py [0:0]

• 11 lines of code
• 3 McCabe index (conditional complexity)

  def __init__(self, normalized_shape: Union[int, Sequence[int]], config: LayerNormConfig):
    super().__init__()
    if config.axis != -1:
      raise NotImplementedError
    if config.center != config.scale:
      raise ValueError(
        f"Center and scale must match in torch, received {config.center}, {config.scale}"
      )
    self.layer = torch.nn.LayerNorm(
      normalized_shape, eps=config.epsilon, elementwise_affine=config.center
    )