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#
# 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.
import torch

from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool
class 			SCREAMING_SNAKE_CASE__  (    lowercase__      ):
      snake_case__    :					int					       =						'''facebook/bart-large-mnli'''
      snake_case__    :					Optional[int]					       =						(
          '''This is a tool that classifies an English text using provided labels. It takes two inputs: `text`, which '''
          '''should be the text to classify, and `labels`, which should be the list of labels to use for classification. '''
          '''It returns the most likely label in the list of provided `labels` for the input text.'''
      )
      snake_case__    :					List[str]					       =						'''text_classifier'''
      snake_case__    :					Tuple					       =						AutoTokenizer
      snake_case__    :					str					       =						AutoModelForSequenceClassification

      snake_case__    :					Optional[Any]					       =						['''text''', ['''text''']]
      snake_case__    :					Tuple					       =						['''text''']
      def 	SCREAMING_SNAKE_CASE							(	self    :	Union[str, Any]					)		->      Optional[int]:
             super().setup()
             a_ :		str							=  self.model.config
             a_ :		Dict							=  -1
             for idx, label in config.idalabel.items():
                    if label.lower().startswith('entail'					):
                           a_ :		Any							=  int(SCREAMING_SNAKE_CASE__					)
             if self.entailment_id == -1:
                    raise ValueError('Could not determine the entailment ID from the model config, please pass it at init.'					)
      def 	SCREAMING_SNAKE_CASE							(	self    :	Union[str, Any]					,							SCREAMING_SNAKE_CASE__    :	Any					,							SCREAMING_SNAKE_CASE__    :	List[Any]					)		->      int:
             a_ :		Tuple							=  labels
             return self.pre_processor(
                 [text] * len(SCREAMING_SNAKE_CASE__					)					,							[F"""This example is {label}""" for label in labels]					,							return_tensors='pt'					,							padding='max_length'					,							)

      def 	SCREAMING_SNAKE_CASE							(	self    :	Tuple					,							SCREAMING_SNAKE_CASE__    :	Union[str, Any]					)		->      str:
             a_ :		str							=  outputs.logits
             a_ :		Optional[Any]							=  torch.argmax(logits[:, 2]					).item()
             return self._labels[label_id]






def 	SCREAMING_SNAKE_CASE_						(      __A			:      list    )     ->		list:

       """simple docstring"""

       a_ :		int							=  len(__A    )
       for _ in range(__A    ):
              for i in range(_ % 2  ,   arr_size - 1  ,   2    ):
                     if arr[i + 1] < arr[i]:
                            a_							,		a_ :		int							=  arr[i + 1], arr[i]

       return arr


if __name__ == "__main__":
   UpperCAmelCase_				:			int   =	list(range(10, 0, -1))
   print(F'Original: {arr}. Sorted: {odd_even_transposition(arr)}')


