code: def decoder_init(m):
      if isinstance(m, torch.nn.Conv1d):
          nn.init.xavier_uniform_(
              m.weight, torch.nn.init.calculate_gain("tanh")
          )
  
imports: import logging
  import torch
  from torch import nn
  from torch.nn import functional
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.modules import LSTMCellWithZoneOut, LocationAttention
label_desc: Use image node_id 2 for calling a global function with example usage: decoder_init(m) without return types