






import argparse

from tax import checkpoints

from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM




def 					lowercase__				(					__snake_case   :							Any					,	__snake_case   :							Tuple					,	__snake_case   :							Dict  ):


					'''simple docstring'''


					UpperCAmelCase_   :				str						=						AutoConfig.from_pretrained(_lowerCamelCase  )
					UpperCAmelCase_   :				Optional[Any]						=						FlaxAutoModelForSeqaSeqLM.from_config(config=_lowerCamelCase  )
					UpperCAmelCase_   :				Optional[int]						=						checkpoints.load_tax_checkpoint(_lowerCamelCase  )

					UpperCAmelCase_   :				int						=						"""wi_0""" in tax_model["""target"""]["""encoder"""]["""layers_0"""]["""mlp"""]

					if config.model_type == "t5":
										UpperCAmelCase_   :				Optional[Any]						=						"""SelfAttention"""
					if config.model_type == "longt5" and config.encoder_attention_type == "local":
										UpperCAmelCase_   :				List[Any]						=						"""LocalSelfAttention"""
					elif config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
										UpperCAmelCase_   :				Tuple						=						"""TransientGlobalSelfAttention"""
					else:
										raise ValueError(
										    'Given config is expected to have `model_type=\'t5\'`, or `model_type=\'longt5` with `encoder_attention_type`'
										    ' attribute with a value from [\'local\', \'transient-global].'  )

					# Encoder
					for layer_index in range(config.num_layers  ):
										UpperCAmelCase_   :				str						=						F"layers_{str(_lowerCamelCase  )}"

										# Self-Attention
										UpperCAmelCase_   :				Optional[int]						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""key"""]["""kernel"""]
										UpperCAmelCase_   :				Tuple						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""out"""]["""kernel"""]
										UpperCAmelCase_   :				Dict						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""query"""]["""kernel"""]
										UpperCAmelCase_   :				int						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""value"""]["""kernel"""]

										# Global input layer norm
										if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
															UpperCAmelCase_   :				Optional[int]						=						tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""T5LayerNorm_0"""]["""scale"""]

										# Layer Normalization
										UpperCAmelCase_   :				int						=						tax_model["""target"""]["""encoder"""][layer_name]["""pre_attention_layer_norm"""]["""scale"""]

										if split_mlp_wi:
															UpperCAmelCase_   :				Dict						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
															UpperCAmelCase_   :				Dict						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
										else:
															UpperCAmelCase_   :				List[str]						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

										UpperCAmelCase_   :				Optional[int]						=						tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

										# Layer Normalization
										UpperCAmelCase_   :				List[Any]						=						tax_model["""target"""]["""encoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

										# Assigning
										UpperCAmelCase_   :				int						=						flax_model.params["""encoder"""]["""block"""][str(_lowerCamelCase  )]["""layer"""]
										UpperCAmelCase_   :				Union[str, Any]						=						tax_attention_key
										UpperCAmelCase_   :				Dict						=						tax_attention_out
										UpperCAmelCase_   :				Optional[Any]						=						tax_attention_query
										UpperCAmelCase_   :				Optional[Any]						=						tax_attention_value

										UpperCAmelCase_   :				Union[str, Any]						=						tax_attention_layer_norm

										# Global input layer norm
										if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
															UpperCAmelCase_   :				Dict						=						tax_global_layer_norm

										if split_mlp_wi:
															UpperCAmelCase_   :				List[str]						=						tax_mlp_wi_a
															UpperCAmelCase_   :				int						=						tax_mlp_wi_a
										else:
															UpperCAmelCase_   :				Tuple						=						tax_mlp_wi

										UpperCAmelCase_   :				Any						=						tax_mlp_wo
										UpperCAmelCase_   :				Optional[int]						=						tax_mlp_layer_norm

										UpperCAmelCase_   :				List[str]						=						flax_model_encoder_layer_block

					# Only for layer 0:
					UpperCAmelCase_   :				Dict						=						tax_model["""target"""]["""encoder"""]["""relpos_bias"""]["""rel_embedding"""].T
					UpperCAmelCase_   :				Dict						=						tax_encoder_rel_embedding

					# Side/global relative position_bias + layer norm
					if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
										UpperCAmelCase_   :				Optional[int]						=						tax_model["""target"""]["""encoder"""]["""side_relpos_bias"""]["""rel_embedding"""].T
										UpperCAmelCase_   :				Dict						=						tax_encoder_global_rel_embedding

					# Assigning
					UpperCAmelCase_   :				Dict						=						tax_model["""target"""]["""encoder"""]["""encoder_norm"""]["""scale"""]
					UpperCAmelCase_   :				str						=						tax_encoder_norm

					# Decoder
					for layer_index in range(config.num_layers  ):
										UpperCAmelCase_   :				Dict						=						F"layers_{str(_lowerCamelCase  )}"

										# Self-Attention
										UpperCAmelCase_   :				Dict						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""key"""]["""kernel"""]
										UpperCAmelCase_   :				List[Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""out"""]["""kernel"""]
										UpperCAmelCase_   :				List[Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""query"""]["""kernel"""]
										UpperCAmelCase_   :				List[str]						=						tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""value"""]["""kernel"""]

										# Layer Normalization
										UpperCAmelCase_   :				Optional[int]						=						tax_model["""target"""]["""decoder"""][layer_name]["""pre_self_attention_layer_norm"""][
										    """scale"""
										]

										# Encoder-Decoder-Attention
										UpperCAmelCase_   :				List[Any]						=						tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]
										UpperCAmelCase_   :				Tuple						=						tax_enc_dec_attention_module["""key"""]["""kernel"""]
										UpperCAmelCase_   :				Optional[int]						=						tax_enc_dec_attention_module["""out"""]["""kernel"""]
										UpperCAmelCase_   :				Any						=						tax_enc_dec_attention_module["""query"""]["""kernel"""]
										UpperCAmelCase_   :				Optional[int]						=						tax_enc_dec_attention_module["""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_   :				str						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
															UpperCAmelCase_   :				str						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
										else:
															UpperCAmelCase_   :				int						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

										UpperCAmelCase_   :				Any						=						tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

										# Layer Normalization
										UpperCAmelCase_   :				Tuple						=						tax_model["""target"""]["""decoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

										# Assigning
										UpperCAmelCase_   :				List[str]						=						flax_model.params["""decoder"""]["""block"""][str(_lowerCamelCase  )]["""layer"""]
										UpperCAmelCase_   :				Optional[int]						=						tax_attention_key
										UpperCAmelCase_   :				Union[str, Any]						=						tax_attention_out
										UpperCAmelCase_   :				Any						=						tax_attention_query
										UpperCAmelCase_   :				List[str]						=						tax_attention_value

										UpperCAmelCase_   :				List[Any]						=						tax_pre_attention_layer_norm

										UpperCAmelCase_   :				List[str]						=						tax_enc_dec_attention_key
										UpperCAmelCase_   :				Union[str, Any]						=						tax_enc_dec_attention_out
										UpperCAmelCase_   :				Dict						=						tax_enc_dec_attention_query
										UpperCAmelCase_   :				int						=						tax_enc_dec_attention_value

										UpperCAmelCase_   :				Optional[Any]						=						tax_cross_layer_norm

										if split_mlp_wi:
															UpperCAmelCase_   :				int						=						tax_mlp_wi_a
															UpperCAmelCase_   :				Any						=						tax_mlp_wi_a
										else:
															UpperCAmelCase_   :				Any						=						tax_mlp_wi

										UpperCAmelCase_   :				str						=						tax_mlp_wo

										UpperCAmelCase_   :				Optional[Any]						=						txa_mlp_layer_norm

										UpperCAmelCase_   :				int						=						flax_model_decoder_layer_block

					# Decoder Normalization
					UpperCAmelCase_   :				Any						=						tax_model["""target"""]["""decoder"""]["""decoder_norm"""]["""scale"""]
					UpperCAmelCase_   :				Optional[Any]						=						txa_decoder_norm

					# Only for layer 0:
					UpperCAmelCase_   :				Union[str, Any]						=						tax_model["""target"""]["""decoder"""]["""relpos_bias"""]["""rel_embedding"""].T
					UpperCAmelCase_   :				Union[str, Any]						=						tax_decoder_rel_embedding

					# Token Embeddings
					UpperCAmelCase_   :				Optional[Any]						=						tax_model["""target"""]["""token_embedder"""]["""embedding"""]
					UpperCAmelCase_   :				Any						=						txa_token_embeddings

					# LM Head (only in v1.1 and LongT5 checkpoints)
					if "logits_dense" in tax_model["target"]["decoder"]:
										UpperCAmelCase_   :				Tuple						=						tax_model["""target"""]["""decoder"""]["""logits_dense"""]["""kernel"""]

					flax_model.save_pretrained(_lowerCamelCase  )
					print('T5X Model was sucessfully converted!'  )


if __name__ == "__main__":
		__UpperCAmelCase     							=						argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    '--t5x_checkpoint_path', default=None, type=str, required=True, help='Path the T5X checkpoint.'
		)
		parser.add_argument('--config_name', default=None, type=str, required=True, help='Config name of LongT5/T5 model.')
		parser.add_argument(
		    '--flax_dump_folder_path', default=None, type=str, required=True, help='Path to the output FLAX model.'
		)
		__UpperCAmelCase     							=						parser.parse_args()
		convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)














def 					lowercase__				(					__snake_case   :							List[str]					,	__snake_case   :							List[str]					,	__snake_case   :							Union[str, Any]					,	__snake_case   :							Optional[int]					,	__snake_case   :							str					,	__snake_case   :							Optional[Any]  ):


					'''simple docstring'''


					if index == r:
										for j in range(__snake_case  ):
															print(data[j]					,	end=' '  )
										print(' '  )
										return
					#  When no more elements are there to put in data[]
					if i >= n:
										return
					# current is included, put next at next location
					UpperCAmelCase_   :				int						=						arr[i]
					combination_util(__snake_case					,	__snake_case					,	__snake_case					,	index + 1					,	__snake_case					,	i + 1  )
					# current is excluded, replace it with
					# next (Note that i+1 is passed, but
					# index is not changed)
					combination_util(__snake_case					,	__snake_case					,	__snake_case					,	__snake_case					,	__snake_case					,	i + 1  )
					# The main function that prints all combinations
					# of size r in arr[] of size n. This function
					# mainly uses combinationUtil()




def 					lowercase__				(					__snake_case   :							List[Any]					,	__snake_case   :							List[Any]					,	__snake_case   :							str  ):


					'''simple docstring'''


					UpperCAmelCase_   :				Union[str, Any]						=						[0] * r
					# Print all combination using temporary array 'data[]'
					combination_util(__snake_case					,	__snake_case					,	__snake_case					,	0					,	__snake_case					,	0  )


if __name__ == "__main__":
		# Driver code to check the function above
		__UpperCAmelCase     							=						[10, 20, 30, 40, 50]
		print_combination(arr, len(arr), 3)
		# This code is contributed by Ambuj sahu






