'''simple docstring'''





import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


UpperCAmelCase_			    =							logging.getLogger(__name__)




@dataclass
@add_start_docstrings(TrainingArguments.__doc__    )
class  __magic_name__  (		_snake_case    ):





   """simple docstring"""




   lowerCAmelCase      :    bool  			=   field(default=_snake_case      ,	metadata={'''help''': '''Whether to use SortishSampler or not.'''}    )
   lowerCAmelCase      :    bool  			=   field(
       default=_snake_case      ,	metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}    )
   lowerCAmelCase      :    Optional[int]  			=   field(
       default=_snake_case      ,	metadata={
           '''help''': (
               '''The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default '''
               '''to the `max_length` value of the model configuration.'''
           )
       }      ,	)
   lowerCAmelCase      :    Optional[int]  			=   field(
       default=_snake_case      ,	metadata={
           '''help''': (
               '''The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default '''
               '''to the `num_beams` value of the model configuration.'''
           )
       }      ,	)
   lowerCAmelCase      :    Optional[Union[str, Path, GenerationConfig]]  			=   field(
       default=_snake_case      ,	metadata={
           '''help''': '''Model id, file path or url pointing to a GenerationConfig json file, to use during prediction.'''
       }      ,	)



   def   lowerCAmelCase						(	self					:  str							):



    """simple docstring"""



    _UpperCamelCase:     List[str]							= super().to_dict()
    for k, v in d.items():
     if isinstance(_lowercase		,  _lowercase							):
      _UpperCamelCase:     str							= v.to_dict()
    return d
# 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  __magic_name__  (		__a    ):





   """simple docstring"""




   lowerCAmelCase      :    Optional[Any]  			=   '''philschmid/bart-large-cnn-samsum'''
   lowerCAmelCase      :    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.'''
   )
   lowerCAmelCase      :    Any  			=   '''summarizer'''
   lowerCAmelCase      :    Tuple  			=   AutoTokenizer
   lowerCAmelCase      :    Optional[Any]  			=   AutoModelForSeqaSeqLM

   lowerCAmelCase      :    Union[str, Any]  			=   ['''text''']
   lowerCAmelCase      :    Dict  			=   ['''text''']



   def   lowerCAmelCase						(	self					:  str		,  _lowercase					:  Union[str, Any]							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  List[Any]		,  _lowercase					:  Optional[Any]							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  int		,  _lowercase					:  List[str]							):



    """simple docstring"""



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