code: def add_args(parser):
      NATransformerModel.add_args(parser)
      parser.add_argument(
          "--train-step",
          type=int,
          help="number of refinement iterations during training",
      )
      parser.add_argument(
          "--dae-ratio",
          type=float,
          help="the probability of switching to the denoising auto-encoder loss",
      )
      parser.add_argument(
          "--stochastic-approx",
          action="store_true",
          help="sampling from the decoder as the inputs for next iteration",
      )
  
file_path: fairseq/fairseq/models/nat/iterative_nonautoregressive_transformer.py
imports: import torch
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.nat import NATransformerModel
label_desc: Use image node_id 1 for calling the IterNATransformerModel obj's underlying member method code with example usage: obj.add_args(parser) without return types