



"""simple docstring"""







import argparse

from tax import checkpoints

from transformers import FlaxTaForConditionalGeneration, TaConfig


def  __SCREAMING_SNAKE_CASE (  __UpperCAmelCase   ,				__UpperCAmelCase   ,				__UpperCAmelCase      ):
		_lowercase				: List[Any]     =   TaConfig.from_pretrained(snake_case_      )
		_lowercase				: Optional[Any]     =   FlaxTaForConditionalGeneration(config=snake_case_      )
		_lowercase				: List[str]     =   checkpoints.load_tax_checkpoint(snake_case_      )

		_lowercase				: int     =   '''wi_0''' in tax_model['''target''']['''encoder''']['''layers_0''']['''mlp''']

		# Encoder
		for layer_index in range(config.num_layers      ):
				_lowercase				: int     =   F"""layers_{str(snake_case_      )}"""

				# Self-Attention
				_lowercase				: Union[str, Any]     =   tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''key''']['''kernel''']
				_lowercase				: Optional[Any]     =   tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''out''']['''kernel''']
				_lowercase				: Any     =   tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''query''']['''kernel''']
				_lowercase				: Tuple     =   tax_model['''target''']['''encoder'''][layer_name]['''attention''']['''value''']['''kernel''']

				# Layer Normalization
				_lowercase				: List[str]     =   tax_model['''target''']['''encoder'''][layer_name]['''pre_attention_layer_norm''']['''scale''']

				if split_mlp_wi:
						_lowercase				: Dict     =   tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi_0''']['''kernel''']
						_lowercase				: str     =   tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi_1''']['''kernel''']
				else:
						_lowercase				: Dict     =   tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wi''']['''kernel''']

				_lowercase				: str     =   tax_model['''target''']['''encoder'''][layer_name]['''mlp''']['''wo''']['''kernel''']

				# Layer Normalization
				_lowercase				: str     =   tax_model['''target''']['''encoder'''][layer_name]['''pre_mlp_layer_norm''']['''scale''']

				# Assigning
				_lowercase				: int     =   tax_attention_key
				_lowercase				: str     =   tax_attention_out
				_lowercase				: Any     =   tax_attention_query
				_lowercase				: Tuple     =   tax_attention_value

				_lowercase				: Tuple     =   tax_attention_layer_norm

				if split_mlp_wi:
						_lowercase				: Optional[int]     =   tax_mlp_wi_a
						_lowercase				: List[str]     =   tax_mlp_wi_a
				else:
						_lowercase				: List[str]     =   tax_mlp_wi

				_lowercase				: Dict     =   tax_mlp_wo
				_lowercase				: int     =   tax_mlp_layer_norm

		# Only for layer 0:
		_lowercase				: Any     =   tax_model['''target''']['''encoder''']['''relpos_bias''']['''rel_embedding'''].T
		_lowercase				: List[str]     =   tax_encoder_rel_embedding

		# Assigning
		_lowercase				: str     =   tax_model['''target''']['''encoder''']['''encoder_norm''']['''scale''']
		_lowercase				: List[Any]     =   tax_encoder_norm

		# Decoder
		for layer_index in range(config.num_decoder_layers      ):
				_lowercase				: int     =   F"""layers_{str(snake_case_      )}"""

				# Self-Attention
				_lowercase				: int     =   tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''key''']['''kernel''']
				_lowercase				: int     =   tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''out''']['''kernel''']
				_lowercase				: List[str]     =   tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''query''']['''kernel''']
				_lowercase				: int     =   tax_model['''target''']['''decoder'''][layer_name]['''self_attention''']['''value''']['''kernel''']

				# Layer Normalization
				_lowercase				: Optional[int]     =   tax_model['''target''']['''decoder'''][layer_name]['''pre_self_attention_layer_norm'''][
				    '''scale'''
				]

				# Encoder-Decoder-Attention
				_lowercase				: str     =   tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''key'''][
				    '''kernel'''
				]
				_lowercase				: int     =   tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''out'''][
				    '''kernel'''
				]
				_lowercase				: Dict     =   tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''query'''][
				    '''kernel'''
				]
				_lowercase				: Any     =   tax_model['''target''']['''decoder'''][layer_name]['''encoder_decoder_attention''']['''value'''][
				    '''kernel'''
				]

				# Layer Normalization
				_lowercase				: Tuple     =   tax_model['''target''']['''decoder'''][layer_name]['''pre_cross_attention_layer_norm''']['''scale''']

				# MLP
				if split_mlp_wi:
						_lowercase				: int     =   tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi_0''']['''kernel''']
						_lowercase				: List[str]     =   tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi_1''']['''kernel''']
				else:
						_lowercase				: Tuple     =   tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wi''']['''kernel''']

				_lowercase				: List[Any]     =   tax_model['''target''']['''decoder'''][layer_name]['''mlp''']['''wo''']['''kernel''']

				# Layer Normalization
				_lowercase				: List[str]     =   tax_model['''target''']['''decoder'''][layer_name]['''pre_mlp_layer_norm''']['''scale''']

				# Assigning
				_lowercase				: Union[str, Any]     =   tax_attention_key
				_lowercase				: List[Any]     =   tax_attention_out
				_lowercase				: Any     =   tax_attention_query
				_lowercase				: Union[str, Any]     =   tax_attention_value

				_lowercase				: str     =   tax_pre_attention_layer_norm

				_lowercase				: Optional[int]     =   tax_enc_dec_attention_key
				_lowercase				: Optional[Any]     =   tax_enc_dec_attention_out
				_lowercase				: List[Any]     =   tax_enc_dec_attention_query
				_lowercase				: Tuple     =   tax_enc_dec_attention_value

				_lowercase				: str     =   tax_cross_layer_norm

				if split_mlp_wi:
						_lowercase				: List[Any]     =   tax_mlp_wi_a
						_lowercase				: str     =   tax_mlp_wi_a
				else:
						_lowercase				: str     =   tax_mlp_wi

				_lowercase				: Optional[int]     =   tax_mlp_wo

				_lowercase				: str     =   txa_mlp_layer_norm

		# Decoder Normalization
		_lowercase				: Optional[Any]     =   tax_model['''target''']['''decoder''']['''decoder_norm''']['''scale''']
		_lowercase				: List[str]     =   txa_decoder_norm

		# Only for layer 0:
		_lowercase				: str     =   tax_model['''target''']['''decoder''']['''relpos_bias''']['''rel_embedding'''].T
		_lowercase				: List[str]     =   tax_decoder_rel_embedding

		# Token Embeddings
		_lowercase				: str     =   tax_model['''target''']['''token_embedder''']['''embedding''']
		_lowercase				: int     =   txa_token_embeddings

		# LM Head (only in v1.1 checkpoints)
		if "logits_dense" in tax_model["target"]["decoder"]:
				_lowercase				: Dict     =   tax_model['''target''']['''decoder''']['''logits_dense''']['''kernel''']

		flax_model.save_pretrained(snake_case_      )
		print("""T5X Model was sucessfully converted!"""      )


if __name__ == "__main__":
		UpperCAmelCase:  List[str]			     =				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."""
		)
		UpperCAmelCase:  Union[str, Any]			     =				parser.parse_args()
		convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)








'''simple docstring'''






import warnings

from .generation import FlaxGenerationMixin

class 	_lowerCAmelCase     (    __A       ):






		'''simple docstring'''
		# warning at import time
		warnings.warn(
		    'Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will '
		    'be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead.'     ,		__A     ,		)



