





"""simple docstring"""


import argparse

import torch

from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						# Construct model
						if gpta_config_file == "":
												UpperCamelCase				:		Union[str, Any]				   =			GPTaConfig()
						else:
												UpperCamelCase				:		Dict				   =			GPTaConfig.from_json_file(SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		Optional[Any]				   =			GPTaModel(SCREAMING_SNAKE_CASE     )

						# Load weights from numpy
						load_tf_weights_in_gpta(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

						# Save pytorch-model
						UpperCamelCase				:		str				   =			pytorch_dump_folder_path + """/""" + WEIGHTS_NAME
						UpperCamelCase				:		Dict				   =			pytorch_dump_folder_path + """/""" + CONFIG_NAME
						print(f"""Save PyTorch model to {pytorch_weights_dump_path}"""     )
						torch.save(model.state_dict()							,     SCREAMING_SNAKE_CASE     )
						print(f"""Save configuration file to {pytorch_config_dump_path}"""     )
						with open(SCREAMING_SNAKE_CASE							,     """w"""							,     encoding="""utf-8"""     ) as f:
												f.write(config.to_json_string()     )


if __name__ == "__main__":
		__magic_name__       :					Tuple						=			argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    """--gpt2_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
		)
		parser.add_argument(
		    """--pytorch_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
		)
		parser.add_argument(
		    """--gpt2_config_file""",
		    default="""""",
		    type=str,
		    help=(
		        """An optional config json file corresponding to the pre-trained OpenAI model. \n"""
		        """This specifies the model architecture."""
		    ),
		)
		__magic_name__       :					int						=			parser.parse_args()
		convert_gpta_checkpoint_to_pytorch(args.gpta_checkpoint_path, args.gpta_config_file, args.pytorch_dump_folder_path)










# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool

class   lowerCAmelCase				(   __UpperCamelCase     ):
 UpperCAmelCase__						=						"""philschmid/bart-large-cnn-samsum"""
 UpperCAmelCase__						=						(
     """This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, """
     """and returns a summary of the text."""
 )
 UpperCAmelCase__						=						"""summarizer"""
 UpperCAmelCase__						=						AutoTokenizer
 UpperCAmelCase__						=						AutoModelForSeqaSeqLM

 UpperCAmelCase__						=						["""text"""]
 UpperCAmelCase__						=						["""text"""]
 def 	A_      ( self    : Tuple     ,	UpperCAmelCase    : List[Any]      )     ->      List[str]:
     return self.pre_processor(UpperCAmelCase     ,	return_tensors='pt'     ,	truncation=UpperCAmelCase      )
 def 	A_      ( self    : Optional[int]     ,	UpperCAmelCase    : Dict      )     ->      str:
     return self.model.generate(**UpperCAmelCase      )[0]







 def 	A_      ( self    : Tuple     ,	UpperCAmelCase    : List[Any]      )     ->      Union[str, Any]:
     return self.pre_processor.decode(UpperCAmelCase     ,	skip_special_tokens=UpperCAmelCase     ,	clean_up_tokenization_spaces=UpperCAmelCase      )





