code: 
  """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						=     threading.Lock()
  _A						=     None
  
  _A						=     {
      "debug": logging.DEBUG,
      "info": logging.INFO,
      "warning": logging.WARNING,
      "error": logging.ERROR,
      "critical": logging.CRITICAL,
  }
  
  _A						=     logging.WARNING
  
  _A						=     True
  
  
  
  
  def 				a__	(	)  ->   List[Any]:
        UpperCAmelCase__ :       str						=						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 				a__	(	)  ->   Optional[Any]:
        return __name__.split("""."""						)[0]
  
  
  
  
  def 				a__	(	)  ->   List[str]:
        return logging.getLogger(_get_library_name()						)
  
  
  
  
  def 				a__	(	)  ->   Any:
        global _default_handler
  
        with _lock:
              if _default_handler:
                    # This library has already configured the library root logger.
                    return
              UpperCAmelCase__ :       int						=						logging.StreamHandler()  # Set sys.stderr as stream.
              UpperCAmelCase__ :       List[str]						=						sys.stderr.flush
  
              # Apply our default configuration to the library root logger.
              UpperCAmelCase__ :       Any						=						_get_library_root_logger()
              library_root_logger.addHandler(_default_handler						)
              library_root_logger.setLevel(_get_default_logging_level()						)
              UpperCAmelCase__ :       int						=						False
  
  
  
  
  def 				a__	(	)  ->   str:
        global _default_handler
  
        with _lock:
              if not _default_handler:
                    return
  
              UpperCAmelCase__ :       str						=						_get_library_root_logger()
              library_root_logger.removeHandler(_default_handler						)
              library_root_logger.setLevel(logging.NOTSET						)
              UpperCAmelCase__ :       str						=						None
  
  
  
  
  def 				a__	(	)  ->   Any:
        return log_levels
  
  
  
  
  def 				a__	(	lowerCAmelCase = None						)  ->   List[str]:
  
  
  
  
  
  
        if name is None:
              UpperCAmelCase__ :       Any						=						_get_library_name()
  
        _configure_library_root_logger()
        return logging.getLogger(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   Optional[int]:
        _configure_library_root_logger()
        return _get_library_root_logger().getEffectiveLevel()
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   Union[str, Any]:
        _configure_library_root_logger()
        _get_library_root_logger().setLevel(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   List[str]:
        return set_verbosity(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   Union[str, Any]:
        return set_verbosity(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   Optional[Any]:
        return set_verbosity(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   str:
        return set_verbosity(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   str:
        _configure_library_root_logger()
  
        assert _default_handler is not None
        _get_library_root_logger().removeHandler(_default_handler						)
  
  
  
  
  def 				a__	(	)  ->   Dict:
        _configure_library_root_logger()
  
        assert _default_handler is not None
        _get_library_root_logger().addHandler(_default_handler						)
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   Optional[int]:
        _configure_library_root_logger()
  
        assert handler is not None
        _get_library_root_logger().addHandler(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   Tuple:
        _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 				a__	(	)  ->   Optional[int]:
        _configure_library_root_logger()
        UpperCAmelCase__ :       Any						=						False
  
  
  
  
  def 				a__	(	)  ->   Dict:
        _configure_library_root_logger()
        UpperCAmelCase__ :       int						=						True
  
  
  
  
  def 				a__	(	)  ->   List[str]:
        UpperCAmelCase__ :       List[str]						=						_get_library_root_logger().handlers
  
        for handler in handlers:
              UpperCAmelCase__ :       str						=						logging.Formatter("""[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s"""						)
              handler.setFormatter(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	)  ->   Optional[int]:
        UpperCAmelCase__ :       Any						=						_get_library_root_logger().handlers
  
        for handler in handlers:
              handler.setFormatter(UpperCamelCase_						)
  
  
  
  
  def 				a__	(	self ,  *lowerCAmelCase ,  **lowerCAmelCase						)  ->   Optional[Any]:
        UpperCAmelCase__ :       int						=						os.getenv("""DIFFUSERS_NO_ADVISORY_WARNINGS""" ,  UpperCamelCase_						)
        if no_advisory_warnings:
              return
        self.warning(*UpperCamelCase_ ,  **UpperCamelCase_						)
  
  
  _A						=     warning_advice
  
  class 			lowerCamelCase  :
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __init__(self       ,					*_lowerCamelCase       ,					**_lowerCamelCase  ):  # pylint: disable=unused-argument
  
  
          """simple docstring"""
  
          UpperCAmelCase__ :       Any						=						args[0] if args else None
  
  
  
    def __iter__(self  ):
  
  
          """simple docstring"""
  
          return iter(self._iterator  )
  
  
  
    def __getattr__(self       ,					_lowerCamelCase  ):
  
  
          """simple docstring"""
  
          def empty_fn(*_lowerCamelCase       ,					**_lowerCamelCase  ):  # pylint: disable=unused-argument
                return
  
          return empty_fn
  
  
  
    def __enter__(self  ):
  
  
          """simple docstring"""
  
          return self
  
  
  
  
    def __exit__(self       ,					_lowerCamelCase       ,					_lowerCamelCase       ,					_lowerCamelCase  ):
  
  
          """simple docstring"""
  
          return
  
  
  
  
  class 			lowerCamelCase  :
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __call__(self       ,					*_lowerCamelCase       ,					**_lowerCamelCase  ):
  
  
          """simple docstring"""
  
          if _tqdm_active:
                return tqdm_lib.tqdm(*__snake_case       ,					**__snake_case  )
          else:
                return EmptyTqdm(*__snake_case       ,					**__snake_case  )
  
  
  
    def    _a			(self       ,					*_lowerCamelCase       ,					**_lowerCamelCase  ):
  
  
          """simple docstring"""
  
          UpperCAmelCase__ :       Any						=						None
          if _tqdm_active:
                return tqdm_lib.tqdm.set_lock(*__snake_case       ,					**__snake_case  )
  
  
  
  
    def    _a			(self  ):
  
  
          """simple docstring"""
  
          if _tqdm_active:
                return tqdm_lib.tqdm.get_lock()
  
  
  
  
  _A						=     _tqdm_cls()
  
  
  
  
  def 				a__	(	)  ->   str:
        global _tqdm_active
        return bool(_tqdm_active						)
  
  
  
  
  def 				a__	(	)  ->   int:
        global _tqdm_active
        UpperCAmelCase__ :       List[str]						=						True
  
  
  
  
  
  def 				a__	(	)  ->   List[str]:
        global _tqdm_active
        UpperCAmelCase__ :       Optional[int]						=						False
  
  
style_context: 
  
  """simple docstring"""
  import argparse
  
  from tax import checkpoints
  
  from transformers import FlaxTaForConditionalGeneration, TaConfig
  
  
  
  
  def 				a__	(	lowerCAmelCase ,  lowerCAmelCase ,  lowerCAmelCase						)  ->   Tuple:
        UpperCAmelCase__ :       int						=						TaConfig.from_pretrained(lowerCAmelCase						)
        UpperCAmelCase__ :       Optional[int]						=						FlaxTaForConditionalGeneration(config=lowerCAmelCase						)
        UpperCAmelCase__ :       int						=						checkpoints.load_tax_checkpoint(lowerCAmelCase						)
  
        UpperCAmelCase__ :       Optional[Any]						=						"""wi_0""" in tax_model["""target"""]["""encoder"""]["""layers_0"""]["""mlp"""]
  
        # Encoder
        for layer_index in range(config.num_layers						):
              UpperCAmelCase__ :       Union[str, Any]						=						F"""layers_{str(lowerCAmelCase						)}"""
  
              # Self-Attention
              UpperCAmelCase__ :       Dict						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""key"""]["""kernel"""]
              UpperCAmelCase__ :       Optional[Any]						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""out"""]["""kernel"""]
              UpperCAmelCase__ :       Dict						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""query"""]["""kernel"""]
              UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""value"""]["""kernel"""]
  
              # Layer Normalization
              UpperCAmelCase__ :       str						=						tax_model["""target"""]["""encoder"""][layer_name]["""pre_attention_layer_norm"""]["""scale"""]
  
              if split_mlp_wi:
                    UpperCAmelCase__ :       int						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
                    UpperCAmelCase__ :       Any						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
              else:
                    UpperCAmelCase__ :       Any						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]
  
              UpperCAmelCase__ :       Tuple						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]
  
              # Layer Normalization
              UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""encoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]
  
              # Assigning
              UpperCAmelCase__ :       str						=						tax_attention_key
              UpperCAmelCase__ :       Union[str, Any]						=						tax_attention_out
              UpperCAmelCase__ :       Union[str, Any]						=						tax_attention_query
              UpperCAmelCase__ :       List[Any]						=						tax_attention_value
  
              UpperCAmelCase__ :       Any						=						tax_attention_layer_norm
  
              if split_mlp_wi:
                    UpperCAmelCase__ :       Any						=						tax_mlp_wi_a
                    UpperCAmelCase__ :       List[Any]						=						tax_mlp_wi_a
              else:
                    UpperCAmelCase__ :       Union[str, Any]						=						tax_mlp_wi
  
              UpperCAmelCase__ :       int						=						tax_mlp_wo
              UpperCAmelCase__ :       List[Any]						=						tax_mlp_layer_norm
  
        # Only for layer 0:
        UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""encoder"""]["""relpos_bias"""]["""rel_embedding"""].T
        UpperCAmelCase__ :       str						=						tax_encoder_rel_embedding
  
        # Assigning
        UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""encoder"""]["""encoder_norm"""]["""scale"""]
        UpperCAmelCase__ :       Optional[Any]						=						tax_encoder_norm
  
        # Decoder
        for layer_index in range(config.num_decoder_layers						):
              UpperCAmelCase__ :       str						=						F"""layers_{str(lowerCAmelCase						)}"""
  
              # Self-Attention
              UpperCAmelCase__ :       List[Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""key"""]["""kernel"""]
              UpperCAmelCase__ :       str						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""out"""]["""kernel"""]
              UpperCAmelCase__ :       Any						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""query"""]["""kernel"""]
              UpperCAmelCase__ :       Union[str, Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""value"""]["""kernel"""]
  
              # Layer Normalization
              UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""decoder"""][layer_name]["""pre_self_attention_layer_norm"""][
                  """scale"""
              ]
  
              # Encoder-Decoder-Attention
              UpperCAmelCase__ :       str						=						tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""key"""][
                  """kernel"""
              ]
              UpperCAmelCase__ :       Union[str, Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""out"""][
                  """kernel"""
              ]
              UpperCAmelCase__ :       Optional[Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""query"""][
                  """kernel"""
              ]
              UpperCAmelCase__ :       Dict						=						tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]["""value"""][
                  """kernel"""
              ]
  
              # Layer Normalization
              UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""decoder"""][layer_name]["""pre_cross_attention_layer_norm"""]["""scale"""]
  
              # MLP
              if split_mlp_wi:
                    UpperCAmelCase__ :       Union[str, Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
                    UpperCAmelCase__ :       int						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
              else:
                    UpperCAmelCase__ :       Union[str, Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]
  
              UpperCAmelCase__ :       Optional[int]						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]
  
              # Layer Normalization
              UpperCAmelCase__ :       Any						=						tax_model["""target"""]["""decoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]
  
              # Assigning
              UpperCAmelCase__ :       Union[str, Any]						=						tax_attention_key
              UpperCAmelCase__ :       str						=						tax_attention_out
              UpperCAmelCase__ :       Tuple						=						tax_attention_query
              UpperCAmelCase__ :       int						=						tax_attention_value
  
              UpperCAmelCase__ :       List[Any]						=						tax_pre_attention_layer_norm
  
              UpperCAmelCase__ :       Union[str, Any]						=						tax_enc_dec_attention_key
              UpperCAmelCase__ :       Optional[int]						=						tax_enc_dec_attention_out
              UpperCAmelCase__ :       List[Any]						=						tax_enc_dec_attention_query
              UpperCAmelCase__ :       Any						=						tax_enc_dec_attention_value
  
              UpperCAmelCase__ :       List[Any]						=						tax_cross_layer_norm
  
              if split_mlp_wi:
                    UpperCAmelCase__ :       Tuple						=						tax_mlp_wi_a
                    UpperCAmelCase__ :       Dict						=						tax_mlp_wi_a
              else:
                    UpperCAmelCase__ :       str						=						tax_mlp_wi
  
              UpperCAmelCase__ :       Tuple						=						tax_mlp_wo
  
              UpperCAmelCase__ :       Any						=						txa_mlp_layer_norm
  
        # Decoder Normalization
        UpperCAmelCase__ :       int						=						tax_model["""target"""]["""decoder"""]["""decoder_norm"""]["""scale"""]
        UpperCAmelCase__ :       Union[str, Any]						=						txa_decoder_norm
  
        # Only for layer 0:
        UpperCAmelCase__ :       List[str]						=						tax_model["""target"""]["""decoder"""]["""relpos_bias"""]["""rel_embedding"""].T
        UpperCAmelCase__ :       Optional[int]						=						tax_decoder_rel_embedding
  
        # Token Embeddings
        UpperCAmelCase__ :       Tuple						=						tax_model["""target"""]["""token_embedder"""]["""embedding"""]
        UpperCAmelCase__ :       int						=						txa_token_embeddings
  
        # LM Head (only in v1.1 checkpoints)
        if "logits_dense" in tax_model["target"]["decoder"]:
              UpperCAmelCase__ :       str						=						tax_model["""target"""]["""decoder"""]["""logits_dense"""]["""kernel"""]
  
        flax_model.save_pretrained(lowerCAmelCase						)
        print("""T5X Model was sucessfully converted!"""						)
  
  
  if __name__ == "__main__":
      _A						=     argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          """--t5x_checkpoint_path""", default=None, type=str, required=True, help="""Path the TX5 checkpoint."""
      )
      parser.add_argument("""--config_name""", default=None, type=str, required=True, help="""Config name of T5 model.""")
      parser.add_argument(
          """--flax_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output FLAX model."""
      )
      _A						=     parser.parse_args()
      convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)
  
  