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: This allows adversarial trainer to turn on and off embedding noising
  layers. In regular training, this mode is off, and it is not included
  in forward pass.
docstr_tok: ["This","allows","adversarial","trainer","to","turn","on","and","off","embedding","noising","layers",".","In","regular","training",",","this","mode","is","off",",","and","it","is","not","included","in","forward","pass","."]
code: def set_embed_noising_mode(self, mode=True):
      """This allows adversarial trainer to turn on and off embedding noising
      layers. In regular training, this mode is off, and it is not included
      in forward pass.
      """
      self.embed_noising_mode = mode
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.onnx.operators
  from fairseq import options, utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, register_model, register_model_architecture
  from fairseq.modules import AdaptiveSoftmax
  from pytorch_translate import attention, rnn_cell, utils, vocab_reduction
  from pytorch_translate.common_layers import ContextEmbedding, DecoderWithOutputProjection, Embedding, Linear, RNNLayer, VariableTracker
  from pytorch_translate.data import data
  from pytorch_translate.multi_model import MultiDecoder, MultiEncoder
  from pytorch_translate.multilingual import MultilingualDecoder, MultilingualEncoder
  from pytorch_translate.ngram import NGramDecoder
  from pytorch_translate.semi_supervised import SemiSupervisedModel
  from pytorch_translate.utils import maybe_cat, maybe_cuda, torch_find
  from torch.nn.utils.rnn import pack_padded_sequence, PackedSequence, pad_packed_sequence
label_desc: Use image node_id 7 for calling the LSTMSequenceEncoder obj's underlying member method code with example usage: obj.set_embed_noising_mode(mode) without return types