class_docstr: Trainer for GAN-based UASR training.
  
  If you'd like to use this trainer, the model must inherit
  espnet.train.abs_gan_espnet_model.AbsGANESPnetModel.
class_docstr_tok: ["Trainer","for","GAN-based","UASR","training",".","If","you","'d","like","to","use","this","trainer",",","the","model","must","inherit","espnet.train.abs_gan_espnet_model.AbsGANESPnetModel","."]
docstr: Build options consumed by train(), eval(), and plot_attention().
docstr_tok: ["Build","options","consumed","by","train","(",")",",","eval","(",")",",","and","plot_attention","(",")","."]
code: def build_options(cls, args: argparse.Namespace) -> TrainerOptions:
      """Build options consumed by train(), eval(), and plot_attention()."""
      assert check_argument_types()
      return build_dataclass(UASRTrainerOptions, args)
  
imports: import argparse
  import dataclasses
  import logging
  import math
  import time
  from contextlib import contextmanager
  from typing import Dict, Iterable, List, Optional, Sequence, Tuple
  import torch
  from packaging.version import parse
  from typeguard import check_argument_types
  from espnet2.schedulers.abs_scheduler import AbsBatchStepScheduler, AbsScheduler
  from espnet2.torch_utils.device_funcs import to_device
  from espnet2.torch_utils.recursive_op import recursive_average
  from espnet2.train.distributed_utils import DistributedOption
  from espnet2.train.reporter import SubReporter
  from espnet2.train.trainer import Trainer, TrainerOptions
  from espnet2.utils.build_dataclass import build_dataclass
  from espnet2.utils.types import str2bool
label_desc: Use image node_id 1 for calling the UASRTrainer obj's underlying member method code with example usage: obj.build_options(cls, args) and returns: build_dataclass