






import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate







@dataclass(frozen=a_  )
class 					lowerCamelCase_  (						a_  ):
							# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
							SCREAMING_SNAKE_CASE_      =      field(default='text-classification'			,    metadata={'include_in_asdict_even_if_is_default': True}  )
							SCREAMING_SNAKE_CASE_      =      Features({'text': Value('string'  )}  )
							SCREAMING_SNAKE_CASE_      =      Features({'labels': ClassLabel}  )
							SCREAMING_SNAKE_CASE_      =      "text"
							SCREAMING_SNAKE_CASE_      =      "labels"
							def 			SCREAMING_SNAKE_CASE_			(    self		:       int				,__lowerCamelCase		:       Dict       ):





								'''simple docstring'''



								if self.label_column not in features:
									raise ValueError(F"""Column {self.label_column} is not present in features."""       )
								if not isinstance(features[self.label_column]				,__lowerCAmelCase       ):
									raise ValueError(F"""Column {self.label_column} is not a ClassLabel."""       )
								a												=      copy.deepcopy(self       )
								a												=      self.label_schema.copy()
								a												=      features[self.label_column]
								a												=      label_schema
								return task_template




							@property
							def 			SCREAMING_SNAKE_CASE_			(    self		:       List[Any]       ):





								'''simple docstring'''



								return {
								    self.text_column: "text",
								    self.label_column: "labels",
								}






"""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 					_A		(			lowerCAmelCase      ):
      snake_case__     :  List[Any]				    =      'philschmid/bart-large-cnn-samsum'
      snake_case__     :  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.'
      )
      snake_case__     :  Tuple				    =      'summarizer'
      snake_case__     :  int				    =      AutoTokenizer
      snake_case__     :  Any				    =      AutoModelForSeqaSeqLM

      snake_case__     :  Optional[int]				    =      ['text']
      snake_case__     :  Optional[int]				    =      ['text']

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.pre_processor(__lowerCAmelCase						,			return_tensors="""pt"""						,			truncation=__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



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







      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



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



