class_docstr: Channel-wise Layer Normalization (cLN).
code: def __init__(self, channel_size, shape="BDT"):
      super().__init__()
      self.gamma = nn.Parameter(
          torch.Tensor(1, channel_size, 1)
      )  # [1, N, 1]
      self.beta = nn.Parameter(
          torch.Tensor(1, channel_size, 1)
      )  # [1, N, 1]
      self.reset_parameters()
      assert shape in ["BDT", "BTD"]
      self.shape = shape
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from espnet2.enh.layers.adapt_layers import make_adapt_layer
label_desc: Use image node_id 1 to create a new ChannelwiseLayerNorm object from inherited base classes: nn with example: obj = ChannelwiseLayerNorm(channel_size, shape)