code: def __init__(
      self,
      n_residue,
      n_skip,
      dilation,
      return_dense_out,
      kernel_size,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.n_residue = n_residue
      self.n_skip = n_skip
      self.dilation = dilation
      self.kernel_size = kernel_size
      self.return_dense_out = return_dense_out
      with self.name_scope():
          self.conv_sigmoid = conv1d(
              in_channels=n_residue,
              channels=n_residue,
              kernel_size=kernel_size,
              dilation=dilation,
              activation="sigmoid",
          )
          self.conv_tanh = conv1d(
              in_channels=n_residue,
              channels=n_residue,
              kernel_size=kernel_size,
              dilation=dilation,
              activation="tanh",
          )
          self.skip = conv1d(
              in_channels=n_residue, channels=n_skip, kernel_size=1
          )
          self.residue = (
              conv1d(
                  in_channels=n_residue,
                  channels=n_residue,
                  kernel_size=1,
              )
              if self.return_dense_out
              else None
          )
  
imports: import math
  from typing import List, Optional
  import mxnet
  from mxnet import gluon
  from mxnet.gluon import nn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.block.feature import FeatureEmbedder
label_desc: Use image node_id 1 to create a new CausalDilatedResidue object from inherited base classes: nn with example: obj = CausalDilatedResidue(n_residue, n_skip, dilation, return_dense_out, kernel_size)