





'''simple docstring'''



# 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 							__lowercase    ( lowerCAmelCase__  ):







	'''simple docstring'''

	a      :			str     =    "philschmid/bart-large-cnn-samsum"
	a      :			int     =    (
	    "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."
	)
	a      :			Optional[Any]     =    "summarizer"
	a      :			str     =    AutoTokenizer
	a      :			Tuple     =    AutoModelForSeqaSeqLM

	a      :			Tuple     =    ["text"]
	a      :			List[Any]     =    ["text"]


	def   _UpperCAmelCase       (self       ,_lowerCamelCase	)							->							str:







				'''simple docstring'''





				return self.pre_processor(_SCREAMING_SNAKE_CASE       ,return_tensors='''pt'''       ,truncation=_SCREAMING_SNAKE_CASE	)


	def   _UpperCAmelCase       (self       ,_lowerCamelCase	)							->							Dict:







				'''simple docstring'''





				return self.model.generate(**_SCREAMING_SNAKE_CASE	)[0]


	def   _UpperCAmelCase       (self       ,_lowerCamelCase	)							->							Optional[Any]:







				'''simple docstring'''





				return self.pre_processor.decode(_SCREAMING_SNAKE_CASE       ,skip_special_tokens=_SCREAMING_SNAKE_CASE       ,clean_up_tokenization_spaces=_SCREAMING_SNAKE_CASE	)












'''simple docstring'''



import numpy as np




def 				_lowerCAmelCase  (			lowerCamelCase_     :					np.array			):
			return 1 / (1 + np.exp(-vector			))




def 				_lowerCAmelCase  (			lowerCamelCase_     :					np.array			):
			return vector * sigmoid(1.7_02 * vector			)


if __name__ == "__main__":
	import doctest

	doctest.testmod()





