
"""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




"""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)

