'''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'''


      UpperCAmelCase_      :      Tuple      							=   '''philschmid/bart-large-cnn-samsum'''
      UpperCAmelCase_      :      List[Any]      							=   (
          '''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_      :      Optional[int]      							=   '''summarizer'''
      UpperCAmelCase_      :      Union[str, Any]      							=   AutoTokenizer
      UpperCAmelCase_      :      Optional[Any]      							=   AutoModelForSeqaSeqLM

      UpperCAmelCase_      :      List[str]      							=   ['''text''']
      UpperCAmelCase_      :      Union[str, Any]      							=   ['''text''']




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Optional[int]:



         '''simple docstring'''



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




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			List[Any]:



         '''simple docstring'''



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




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Tuple:



         '''simple docstring'''



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





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase__     :	Union[str, Any]				=			{'tokenization_byt5': ['ByT5Tokenizer']}


if TYPE_CHECKING:
  from .tokenization_byta import ByTaTokenizer
else:
  import sys

  UpperCamelCase__     :	List[str]				=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




