class_docstr: RNN encoder using nn.LSTM for cuDNN support / ONNX exportability.
class_docstr_tok: ["RNN","encoder","using","nn.LSTM","for","cuDNN","support","\/","ONNX","exportability","."]
docstr: Maximum output length supported by the decoder.
docstr_tok: ["Maximum","output","length","supported","by","the","decoder","."]
code: def max_positions(self):
      """Maximum output length supported by the decoder."""
      return int(1e5)
  
file_path: pytext/pytext/models/seq_models/rnn_encoder.py
imports: from typing import Dict, List, Tuple
  import torch
  import torch.nn.functional
  from pytext.config import ConfigBase
  from pytext.utils.usage import log_class_usage
  from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
  from .base import PyTextSeq2SeqModule
label_desc: Use image node_id 4 for calling the LSTMSequenceEncoder obj's underlying member method code with example usage: obj.max_positions() and returns: int