'''simple docstring'''
import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


_A		:			Union[str, Any]	      =threading.Lock()
_A		:			Optional[logging.Handler]	      =None

_A		:			str	      ={
    '''debug''': logging.DEBUG,
    '''info''': logging.INFO,
    '''warning''': logging.WARNING,
    '''error''': logging.ERROR,
    '''critical''': logging.CRITICAL,
}

_A		:			Dict	      =logging.WARNING

_A		:			List[str]	      =True







def 							__UpperCamelCase   (				)       ->  Optional[Any]:
  lowercase							:       Optional[Any]											=      os.getenv('''DIFFUSERS_VERBOSITY'''   ,      __UpperCAmelCase )
  if env_level_str:
    if env_level_str in log_levels:
      return log_levels[env_level_str]
    else:
      logging.getLogger().warning(
          f"""Unknown option DIFFUSERS_VERBOSITY={env_level_str}, """
          f"""has to be one of: { ", ".join(log_levels.keys() ) }""" )
  return _default_log_level







def 							__UpperCamelCase   (				)       ->  str:
  return __name__.split('''.''' )[0]







def 							__UpperCamelCase   (				)       ->  logging.Logger:
  return logging.getLogger(_get_library_name() )







def 							__UpperCamelCase   (				)       ->  None:
  global _default_handler

  with _lock:
    if _default_handler:
      # This library has already configured the library root logger.
      return
    lowercase							:       List[Any]											=      logging.StreamHandler()  # Set sys.stderr as stream.
    lowercase							:       Optional[Any]											=      sys.stderr.flush

    # Apply our default configuration to the library root logger.
    lowercase							:       Optional[int]											=      _get_library_root_logger()
    library_root_logger.addHandler(_default_handler )
    library_root_logger.setLevel(_get_default_logging_level() )
    lowercase							:       List[Any]											=      False







def 							__UpperCamelCase   (				)       ->  None:
  global _default_handler

  with _lock:
    if not _default_handler:
      return

    lowercase							:       Optional[Any]											=      _get_library_root_logger()
    library_root_logger.removeHandler(_default_handler )
    library_root_logger.setLevel(logging.NOTSET )
    lowercase							:       Union[str, Any]											=      None







def 							__UpperCamelCase   (				)       ->  List[str]:
  return log_levels







def 							__UpperCamelCase   (				__UpperCAmelCase     :				Optional[str] = None )       ->  logging.Logger:

  if name is None:
    lowercase							:       Optional[Any]											=      _get_library_name()

  _configure_library_root_logger()
  return logging.getLogger(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  int:
  _configure_library_root_logger()
  return _get_library_root_logger().getEffectiveLevel()







def 							__UpperCamelCase   (				__UpperCAmelCase     :				int )       ->  None:
  _configure_library_root_logger()
  _get_library_root_logger().setLevel(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  List[str]:
  return set_verbosity(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  Union[str, Any]:
  return set_verbosity(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  Optional[int]:
  return set_verbosity(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  Optional[int]:
  return set_verbosity(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  None:
  _configure_library_root_logger()

  assert _default_handler is not None
  _get_library_root_logger().removeHandler(_default_handler )







def 							__UpperCamelCase   (				)       ->  None:
  _configure_library_root_logger()

  assert _default_handler is not None
  _get_library_root_logger().addHandler(_default_handler )







def 							__UpperCamelCase   (				__UpperCAmelCase     :				logging.Handler )       ->  None:
  _configure_library_root_logger()

  assert handler is not None
  _get_library_root_logger().addHandler(__UpperCAmelCase )







def 							__UpperCamelCase   (				__UpperCAmelCase     :				logging.Handler )       ->  None:
  _configure_library_root_logger()

  assert handler is not None and handler not in _get_library_root_logger().handlers
  _get_library_root_logger().removeHandler(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  None:
  _configure_library_root_logger()
  lowercase							:       int											=      False







def 							__UpperCamelCase   (				)       ->  None:
  _configure_library_root_logger()
  lowercase							:       List[Any]											=      True







def 							__UpperCamelCase   (				)       ->  None:
  lowercase							:       Optional[Any]											=      _get_library_root_logger().handlers

  for handler in handlers:
    lowercase							:       Tuple											=      logging.Formatter('''[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s''' )
    handler.setFormatter(__UpperCAmelCase )







def 							__UpperCamelCase   (				)       ->  None:
  lowercase							:       int											=      _get_library_root_logger().handlers

  for handler in handlers:
    handler.setFormatter(__UpperCAmelCase )







def 							__UpperCamelCase   (				self     :				int   ,      *__UpperCAmelCase     :				Tuple   ,      **__UpperCAmelCase     :				List[str] )       ->  Dict:
  lowercase							:       Optional[Any]											=      os.getenv('''DIFFUSERS_NO_ADVISORY_WARNINGS'''   ,      __UpperCAmelCase )
  if no_advisory_warnings:
    return
  self.warning(*__UpperCAmelCase   ,      **__UpperCAmelCase )


_A		:			List[Any]	      =warning_advice




class _lowerCAmelCase :







      def __init__(     self     ,						*lowercase     ,						**lowercase    ):  # pylint: disable=unused-argument
        lowercase							:       Dict											=      args[0] if args else None







      def __iter__(     self    ):
        return iter(self._iterator    )







      def __getattr__(     self     ,						lowercase    ):

        def empty_fn(*lowercase     ,						**lowercase    ):  # pylint: disable=unused-argument
          return

        return empty_fn







      def __enter__(     self    ):
        return self







      def __exit__(     self     ,						lowercase     ,						lowercase     ,						lowercase    ):
        return





class _lowerCAmelCase :







      def __call__(     self     ,						*lowercase     ,						**lowercase    ):
        if _tqdm_active:
          return tqdm_lib.tqdm(*lowercase     ,						**lowercase    )
        else:
          return EmptyTqdm(*lowercase     ,						**lowercase    )







      def     lowerCamelCase__			(     self     ,						*lowercase     ,						**lowercase    ):
        lowercase							:       str											=      None
        if _tqdm_active:
          return tqdm_lib.tqdm.set_lock(*lowercase     ,						**lowercase    )







      def     lowerCamelCase__			(     self    ):
        if _tqdm_active:
          return tqdm_lib.tqdm.get_lock()





_A		:			Optional[int]	      =_tqdm_cls()







def 							__UpperCamelCase   (				)       ->  bool:
  global _tqdm_active
  return bool(_tqdm_active )







def 							__UpperCamelCase   (				)       ->  Tuple:
  global _tqdm_active
  lowercase							:       Optional[Any]											=      True







def 							__UpperCamelCase   (				)       ->  List[Any]:
  global _tqdm_active
  lowercase							:       int											=      False
'''simple docstring'''
import argparse

import torch

from transformers import ElectraConfig, ElectraForMaskedLM, ElectraForPreTraining, load_tf_weights_in_electra
from transformers.utils import logging


logging.set_verbosity_info()







def 							__UpperCamelCase   (				__UpperCAmelCase     :				Optional[Any]   ,      __UpperCAmelCase     :				Tuple   ,      __UpperCAmelCase     :				Union[str, Any]   ,      __UpperCAmelCase     :				List[str] )       ->  List[str]:
  # Initialise PyTorch model
  lowercase							:       Any											=      ElectraConfig.from_json_file(__UpperCAmelCase )
  print(f"""Building PyTorch model from configuration: {config}""" )

  if discriminator_or_generator == "discriminator":
    lowercase							:       Union[str, Any]											=      ElectraForPreTraining(__UpperCAmelCase )
  elif discriminator_or_generator == "generator":
    lowercase							:       Tuple											=      ElectraForMaskedLM(__UpperCAmelCase )
  else:
    raise ValueError('''The discriminator_or_generator argument should be either \'discriminator\' or \'generator\'''' )

  # Load weights from tf checkpoint
  load_tf_weights_in_electra(
      __UpperCAmelCase   ,      __UpperCAmelCase   ,      __UpperCAmelCase   ,      discriminator_or_generator=__UpperCAmelCase )

  # Save pytorch-model
  print(f"""Save PyTorch model to {pytorch_dump_path}""" )
  torch.save(model.state_dict()   ,      __UpperCAmelCase )


if __name__ == "__main__":
 _A		:			str	      =argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
 )
 parser.add_argument(
     '''--config_file''',
     default=None,
     type=str,
     required=True,
     help='''The config json file corresponding to the pre-trained model. \nThis specifies the model architecture.''',
 )
 parser.add_argument(
     '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
 )
 parser.add_argument(
     '''--discriminator_or_generator''',
     default=None,
     type=str,
     required=True,
     help=(
         '''Whether to export the generator or the discriminator. Should be a string, either \'discriminator\' or '''
         '''\'generator\'.'''
     ),
 )
 _A		:			Any	      =parser.parse_args()
 convert_tf_checkpoint_to_pytorch(
     args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path, args.discriminator_or_generator
 )