docstr: Set the hyper-parameters and build the layers.
docstr_tok: ["Set","the","hyper-parameters","and","build","the","layers","."]
code: def __init__(
      self,
      embed_size,
      hidden_size,
      vocab_size,
      num_layers,
      max_seq_length=20,
  ):
      """Set the hyper-parameters and build the layers."""
      super(DecoderRNN, self).__init__()
      self.embed = nn.Embedding(vocab_size, embed_size)
      self.lstm = nn.LSTM(
          embed_size, hidden_size, num_layers, batch_first=True
      )
      self.linear = nn.Linear(hidden_size, vocab_size)
      self.max_seg_length = max_seq_length
  
file_path: pytorch-tutorial/tutorials/03-advanced/image_captioning/model.py
imports: import torch
  import torch.nn
  import torchvision.models
  from torch.nn.utils.rnn import pack_padded_sequence
label_desc: Use image node_id 1 to create a new DecoderRNN object from inherited base classes: nn with example: obj = DecoderRNN(embed_size, hidden_size, vocab_size, num_layers, max_seq_length)