code: def __init__(self, in_dim, out_dim, **kwargs):
      super().__init__()
  
      self.language_lstm = nn.LSTMCell(
          in_dim + kwargs["hidden_dim"], kwargs["hidden_dim"], bias=True
      )
      self.fc = weight_norm(nn.Linear(kwargs["hidden_dim"], out_dim))
      self.dropout = nn.Dropout(p=kwargs["dropout"])
      self.init_weights(kwargs["fc_bias_init"])
  
file_path: mmf/mmf/modules/decoders.py
imports: import torch
  from mmf.common.registry import registry
  from torch import nn
  from torch.nn.utils.weight_norm import weight_norm
label_desc: Use image node_id 1 to create a new LanguageDecoder object from inherited base classes: nn with example: obj = LanguageDecoder(in_dim, out_dim)