class_docstr: Optim wrapper that implements rate.
class_docstr_tok: ["Optim","wrapper","that","implements","rate","."]
docstr: Construct an NoamOpt object.
docstr_tok: ["Construct","an","NoamOpt","object","."]
code: def __init__(self, model_size, factor, warmup, optimizer):
      """Construct an NoamOpt object."""
      self.optimizer = optimizer
      self._step = 0
      self.warmup = warmup
      self.factor = factor
      self.model_size = model_size
      self._rate = 0
  
file_path: espnet/espnet/nets/pytorch_backend/transformer/optimizer.py
imports: import torch
label_desc: Use image node_id 1 to create a new NoamOpt object from inherited base classes: object with example: obj = NoamOpt(model_size, factor, warmup, optimizer)