
'''simple docstring'''







import argparse
import os
from pathlib import Path
from typing import Dict

import tensorflow as tf
import torch
from tqdm import tqdm

from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_params


_snake_case				:   List[str]     =				[
    # replace left string with right string to get the relevant state_dict key (identical state dict to bart)
    ["""memory_attention""", """encoder_attn"""],
    ["""attention""", """attn"""],
    ["""/""", """."""],
    [""".LayerNorm.gamma""", """_layer_norm.weight"""],
    [""".LayerNorm.beta""", """_layer_norm.bias"""],
    ["""r.layer_""", """r.layers."""],
    ["""output_proj""", """out_proj"""],
    ["""ffn.dense_1.""", """fc2."""],
    ["""ffn.dense.""", """fc1."""],
    ["""ffn_layer_norm""", """final_layer_norm"""],
    ["""kernel""", """weight"""],
    ["""encoder_layer_norm.""", """encoder.layer_norm."""],
    ["""decoder_layer_norm.""", """decoder.layer_norm."""],
    ["""embeddings.weights""", """shared.weight"""],
]



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]  ):
						for pegasus_name, hf_name in PATTERNS:
												_SCREAMING_SNAKE_CASE				= k.replace(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
						return k



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   int  ):
						_SCREAMING_SNAKE_CASE				= DEFAULTS.copy()
						cfg_kwargs.update(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= PegasusConfig(**_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= PegasusForConditionalGeneration(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= torch_model.model.state_dict()
						_SCREAMING_SNAKE_CASE				= {}
						for k, v in tf_weights.items():
												_SCREAMING_SNAKE_CASE				= rename_state_dict_key(_SCREAMING_SNAKE_CASE  )
												if new_k not in sd:
																		raise ValueError(F'could not find new key {new_k} in state dict. (converted from {k})'  )

												if "dense" in k or "proj" in new_k:
																		_SCREAMING_SNAKE_CASE				= v.T
												_SCREAMING_SNAKE_CASE				= torch.tensor(_SCREAMING_SNAKE_CASE	,			dtype=sd[new_k].dtype  )
												assert v.shape == sd[new_k].shape, F'{new_k}, {k}, {v.shape}, {sd[new_k].shape}'
						# make sure embedding.padding_idx is respected
						_SCREAMING_SNAKE_CASE				= torch.zeros_like(mapping["shared.weight"][cfg.pad_token_id + 1]  )
						_SCREAMING_SNAKE_CASE				= mapping["shared.weight"]
						_SCREAMING_SNAKE_CASE				= mapping["shared.weight"]
						_SCREAMING_SNAKE_CASE				= {k: torch.zeros_like(_SCREAMING_SNAKE_CASE  ) for k, v in sd.items() if k.endswith("bias"  ) and k not in mapping}
						mapping.update(**_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= torch_model.model.load_state_dict(_SCREAMING_SNAKE_CASE	,			strict=_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= [
						    k for k in missing if k not in ["encoder.embed_positions.weight", "decoder.embed_positions.weight"]
						]
						assert unexpected_missing == [], F'no matches found for the following torch keys {unexpected_missing}'
						assert extra == [], F'no matches found for the following tf keys {extra}'
						return torch_model



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Any="./ckpt/aeslc/model.ckpt-32000"  ):
						_SCREAMING_SNAKE_CASE				= tf.train.list_variables(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= {}
						_SCREAMING_SNAKE_CASE				= ["Adafactor", "global_step"]
						for name, shape in tqdm(_SCREAMING_SNAKE_CASE	,			desc="converting tf checkpoint to dict"  ):
												_SCREAMING_SNAKE_CASE				= any(pat in name for pat in ignore_name  )
												if skip_key:
																		continue
												_SCREAMING_SNAKE_CASE				= tf.train.load_variable(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
												_SCREAMING_SNAKE_CASE				= array
						return tf_weights



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]	,			_SCREAMING_SNAKE_CASE		:   List[Any]  ):
						# save tokenizer first
						_SCREAMING_SNAKE_CASE				= Path(_SCREAMING_SNAKE_CASE  ).parent.name
						_SCREAMING_SNAKE_CASE				= task_specific_params[F'summarization_{dataset}']["max_position_embeddings"]
						_SCREAMING_SNAKE_CASE				= PegasusTokenizer.from_pretrained("sshleifer/pegasus"	,			model_max_length=_SCREAMING_SNAKE_CASE  )
						assert tok.model_max_length == desired_max_model_length
						tok.save_pretrained(_SCREAMING_SNAKE_CASE  )

						# convert model
						_SCREAMING_SNAKE_CASE				= get_tf_weights_as_numpy(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= task_specific_params[F'summarization_{dataset}']
						if dataset == "large":
												_SCREAMING_SNAKE_CASE				= task_specific_params
						_SCREAMING_SNAKE_CASE				= convert_pegasus(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
						torch_model.save_pretrained(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= torch_model.state_dict()
						sd.pop("model.decoder.embed_positions.weight"  )
						sd.pop("model.encoder.embed_positions.weight"  )
						torch.save(_SCREAMING_SNAKE_CASE	,			Path(_SCREAMING_SNAKE_CASE  ) / "pytorch_model.bin"  )


if __name__ == "__main__":
						_snake_case				:   Dict     =				argparse.ArgumentParser()
						# Required parameters
						parser.add_argument("""tf_ckpt_path""", type=str, help="""passed to tf.train.list_variables""")
						parser.add_argument("""save_dir""", default=None, type=str, help="""Path to the output PyTorch model.""")
						_snake_case				:   Optional[Any]     =				parser.parse_args()
						if args.save_dir is None:
												_snake_case				:   str     =				Path(args.tf_ckpt_path).parent.name
												_snake_case				:   Optional[int]     =				os.path.join("""pegasus""", dataset)
						convert_pegasus_ckpt_to_pytorch(args.tf_ckpt_path, args.save_dir)

'''simple docstring'''







from ..utils import DummyObject, requires_backends


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Dict       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Tuple       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					str       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Tuple       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					List[Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Any       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Any       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					int       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					str       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Any       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Any       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Union[str, Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					str       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Union[str, Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					int       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Dict       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					List[str]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[int]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Dict       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Dict       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					str       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Tuple       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Union[str, Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					str       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[int]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Optional[Any]       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )


class 			lowerCAmelCase (				metaclass=__UpperCAmelCase			):
		a							:					Dict       =					["""sentencepiece"""]




		def __init__(				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								requires_backends(self					,						["sentencepiece"]      )