





import argparse

from tax import checkpoints

from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM





def  __magic_name__  (				lowercase				,       lowercase				,       lowercase				)				-> Optional[int]:

							"""simple docstring"""



							lowercase_	:   Dict  				=     AutoConfig.from_pretrained(lowercase				)
							lowercase_	:   Tuple  				=     FlaxAutoModelForSeqaSeqLM.from_config(config=lowercase				)
							lowercase_	:   Any  				=     checkpoints.load_tax_checkpoint(lowercase				)

							lowercase_	:   Tuple  				=     """wi_0""" in tax_model["""target"""]["""encoder"""]["""layers_0"""]["""mlp"""]

							if config.model_type == "t5":
														lowercase_	:   List[str]  				=     """SelfAttention"""
							if config.model_type == "longt5" and config.encoder_attention_type == "local":
														lowercase_	:   Tuple  				=     """LocalSelfAttention"""
							elif config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
														lowercase_	:   List[Any]  				=     """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				):
														lowercase_	:   Tuple  				=     f"""layers_{str(lowercase				)}"""

														# Self-Attention
														lowercase_	:   Optional[int]  				=     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""key"""]["""kernel"""]
														lowercase_	:   Optional[int]  				=     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""out"""]["""kernel"""]
														lowercase_	:   List[str]  				=     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""query"""]["""kernel"""]
														lowercase_	:   Union[str, Any]  				=     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":
																					lowercase_	:   Tuple  				=     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""T5LayerNorm_0"""]["""scale"""]

														# Layer Normalization
														lowercase_	:   Any  				=     tax_model["""target"""]["""encoder"""][layer_name]["""pre_attention_layer_norm"""]["""scale"""]

														if split_mlp_wi:
																					lowercase_	:   str  				=     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
																					lowercase_	:   Union[str, Any]  				=     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
														else:
																					lowercase_	:   int  				=     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

														lowercase_	:   Optional[Any]  				=     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

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

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

														lowercase_	:   Optional[int]  				=     tax_attention_layer_norm

														# Global input layer norm
														if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
																					lowercase_	:   Union[str, Any]  				=     tax_global_layer_norm

														if split_mlp_wi:
																					lowercase_	:   Tuple  				=     tax_mlp_wi_a
																					lowercase_	:   Union[str, Any]  				=     tax_mlp_wi_a
														else:
																					lowercase_	:   Tuple  				=     tax_mlp_wi

														lowercase_	:   List[str]  				=     tax_mlp_wo
														lowercase_	:   List[str]  				=     tax_mlp_layer_norm

														lowercase_	:   Dict  				=     flax_model_encoder_layer_block

							# Only for layer 0:
							lowercase_	:   Tuple  				=     tax_model["""target"""]["""encoder"""]["""relpos_bias"""]["""rel_embedding"""].T
							lowercase_	:   int  				=     tax_encoder_rel_embedding

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

							# Assigning
							lowercase_	:   Optional[Any]  				=     tax_model["""target"""]["""encoder"""]["""encoder_norm"""]["""scale"""]
							lowercase_	:   Optional[int]  				=     tax_encoder_norm

							# Decoder
							for layer_index in range(config.num_layers				):
														lowercase_	:   Tuple  				=     f"""layers_{str(lowercase				)}"""

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

														# Layer Normalization
														lowercase_	:   List[str]  				=     tax_model["""target"""]["""decoder"""][layer_name]["""pre_self_attention_layer_norm"""][
														    """scale"""
														]

														# Encoder-Decoder-Attention
														lowercase_	:   Optional[int]  				=     tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]
														lowercase_	:   Any  				=     tax_enc_dec_attention_module["""key"""]["""kernel"""]
														lowercase_	:   Optional[int]  				=     tax_enc_dec_attention_module["""out"""]["""kernel"""]
														lowercase_	:   str  				=     tax_enc_dec_attention_module["""query"""]["""kernel"""]
														lowercase_	:   Union[str, Any]  				=     tax_enc_dec_attention_module["""value"""]["""kernel"""]

														# Layer Normalization
														lowercase_	:   Union[str, Any]  				=     tax_model["""target"""]["""decoder"""][layer_name]["""pre_cross_attention_layer_norm"""]["""scale"""]

														# MLP
														if split_mlp_wi:
																					lowercase_	:   Any  				=     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
																					lowercase_	:   Optional[int]  				=     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
														else:
																					lowercase_	:   int  				=     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

														lowercase_	:   List[str]  				=     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

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

														# Assigning
														lowercase_	:   Optional[Any]  				=     flax_model.params["""decoder"""]["""block"""][str(lowercase				)]["""layer"""]
														lowercase_	:   Dict  				=     tax_attention_key
														lowercase_	:   List[str]  				=     tax_attention_out
														lowercase_	:   Tuple  				=     tax_attention_query
														lowercase_	:   Dict  				=     tax_attention_value

														lowercase_	:   Optional[int]  				=     tax_pre_attention_layer_norm

														lowercase_	:   Dict  				=     tax_enc_dec_attention_key
														lowercase_	:   Dict  				=     tax_enc_dec_attention_out
														lowercase_	:   Any  				=     tax_enc_dec_attention_query
														lowercase_	:   str  				=     tax_enc_dec_attention_value

														lowercase_	:   Any  				=     tax_cross_layer_norm

														if split_mlp_wi:
																					lowercase_	:   Union[str, Any]  				=     tax_mlp_wi_a
																					lowercase_	:   Union[str, Any]  				=     tax_mlp_wi_a
														else:
																					lowercase_	:   Tuple  				=     tax_mlp_wi

														lowercase_	:   Optional[int]  				=     tax_mlp_wo

														lowercase_	:   Any  				=     txa_mlp_layer_norm

														lowercase_	:   Dict  				=     flax_model_decoder_layer_block

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

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

							# Token Embeddings
							lowercase_	:   Optional[int]  				=     tax_model["""target"""]["""token_embedder"""]["""embedding"""]
							lowercase_	:   Tuple  				=     txa_token_embeddings

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

							flax_model.save_pretrained(lowercase				)
							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)






import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp





def  __magic_name__  (				)				-> str:

							"""simple docstring"""



							lowercase_	:   Optional[int]  				=     ArgumentParser(
							    description=(
							        """PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes"""
							    )				)

							# Optional arguments for the launch helper
							parser.add_argument("""--num_cores"""				,       type=lowercase				,       default=1				,       help="""Number of TPU cores to use (1 or 8)."""				)

							# positional
							parser.add_argument(
							    """training_script"""				,       type=lowercase				,       help=(
							        """The full path to the single TPU training """
							        """program/script to be launched in parallel, """
							        """followed by all the arguments for the """
							        """training script"""
							    )				,       )

							# rest from the training program
							parser.add_argument("""training_script_args"""				,       nargs=lowercase				)

							return parser.parse_args()





def  __magic_name__  (				)				-> List[Any]:

							"""simple docstring"""



							lowercase_	:   Union[str, Any]  				=     parse_args()

							# Import training_script as a module.
							lowercase_	:   List[Any]  				=     Path(args.training_script				)
							sys.path.append(str(script_fpath.parent.resolve()				)				)
							lowercase_	:   Tuple  				=     script_fpath.stem
							lowercase_	:   List[str]  				=     importlib.import_module(lowercase				)

							# Patch sys.argv
							lowercase_	:   Optional[int]  				=     [args.training_script] + args.training_script_args + ["""--tpu_num_cores""", str(args.num_cores				)]

							xmp.spawn(mod._mp_fn				,       args=()				,       nprocs=args.num_cores				)


if __name__ == "__main__":
							main()