class_docstr: SEANet decoder.
  
  Args:
      channels (int): Audio channels.
      dimension (int): Intermediate representation dimension.
      n_filters (int): Base width for the model.
      n_residual_layers (int): nb of residual layers.
      ratios (Sequence[int]): kernel size and stride ratios.
      activation (str): Activation function.
      activation_params (dict): Parameters to provide to the activation function.
      final_activation (str): Final activation function after all convolutions.
      final_activation_params (dict): Parameters to provide to the activation function.
      norm (str): Normalization method.
      norm_params (dict): Parameters to provide to the underlying normalization used along with the convolution.
      kernel_size (int): Kernel size for the initial convolution.
      last_kernel_size (int): Kernel size for the initial convolution.
      residual_kernel_size (int): Kernel size for the residual layers.
      dilation_base (int): How much to increase the dilation with each layer.
      causal (bool): Whether to use fully causal convolution.
      pad_mode (str): Padding mode for the convolutions.
      true_skip (bool): Whether to use true skip connection or a simple.
          (streamable) convolution as the skip connection in the residual network blocks.
      compress (int): Reduced dimensionality in residual branches (from Demucs v3).
      lstm (int): Number of LSTM layers at the end of the encoder.
      disable_norm_outer_blocks (int): Number of blocks for which we don't apply norm.
          For the decoder, it corresponds to the N last blocks.
      trim_right_ratio (float): Ratio for trimming at the right of the transposed convolution under the causal setup.
          If equal to 1.0, it means that all the trimming is done at the right.
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code: def forward(self, z):
      y = self.model(z)
      return y
  
file_path: audiocraft/audiocraft/modules/seanet.py
imports: import typing
  import numpy
  import torch.nn
  from .conv import StreamableConv1d, StreamableConvTranspose1d
  from .lstm import StreamableLSTM
label_desc: Use image node_id 2 for calling the SEANetDecoder obj's underlying member method code with example usage: obj.forward(z) and returns: y