






'''simple docstring'''
a_					=	[0, 2, 4, 6, 8]
a_					=	[1, 3, 5, 7, 9]





def 	_a(					UpperCamelCase__			:  int,		UpperCamelCase__			:  int,		UpperCamelCase__			:  list[int],		UpperCamelCase__			:  int							):




      '''simple docstring'''






      if remaining_length == 0:
            if digits[0] == 0 or digits[-1] == 0:
                  return 0

            for i in range(length // 2 - 1,		-1,		-1							):
                  remainder += digits[i] + digits[length - i - 1]

                  if remainder % 2 == 0:
                        return 0

                  remainder //= 1_0

            return 1

      if remaining_length == 1:
            if remainder % 2 == 0:
                  return 0

            SCREAMING_SNAKE_CASE__       :			List[Any]													=0
            for digit in range(1_0							):
                  SCREAMING_SNAKE_CASE__       :			List[Any]													=digit
                  result += reversible_numbers(
                      0,		(remainder + 2 * digit) // 1_0,		UpperCamelCase__,		UpperCamelCase__							)
            return result

      SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=0
      for digita in range(1_0							):
            SCREAMING_SNAKE_CASE__       :			Tuple													=digita

            if (remainder + digita) % 2 == 0:
                  SCREAMING_SNAKE_CASE__       :			str													=ODD_DIGITS
            else:
                  SCREAMING_SNAKE_CASE__       :			Optional[int]													=EVEN_DIGITS

            for digita in other_parity_digits:
                  SCREAMING_SNAKE_CASE__       :			Optional[Any]													=digita
                  result += reversible_numbers(
                      remaining_length - 2,		(remainder + digita + digita) // 1_0,		UpperCamelCase__,		UpperCamelCase__,		)
      return result





def 	_a(					UpperCamelCase__			:  int = 9							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[Any]													=0
      for length in range(1,		max_power + 1							):
            result += reversible_numbers(UpperCamelCase__,		0,		[0] * length,		UpperCamelCase__							)
      return result


if __name__ == "__main__":
  print(F'''{solution() = }''')







'''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.
import torch

from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool






class        __SCREAMING_SNAKE_CASE (     lowerCamelCase			):
 snake_case_												=							"""facebook/bart-large-mnli"""
 snake_case_												=							(
     """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_												=							"""text_classifier"""
 snake_case_												=							AutoTokenizer
 snake_case_												=							AutoModelForSequenceClassification

 snake_case_												=							["""text""", ["""text"""]]
 snake_case_												=							["""text"""]




 def        __magic_name__		( self		:							Any )		->  Any:
       super().setup()
       SCREAMING_SNAKE_CASE__       :			int													=self.model.config
       SCREAMING_SNAKE_CASE__       :			int													=-1
       for idx, label in config.idalabel.items():
             if label.lower().startswith('''entail''' ):
                   SCREAMING_SNAKE_CASE__       :			Any													=int(__lowercase )
       if self.entailment_id == -1:
             raise ValueError('''Could not determine the entailment ID from the model config, please pass it at init.''' )




 def        __magic_name__		( self		:							str   , __lowercase		:							Any   , __lowercase		:							Optional[Any] )		->  Optional[Any]:
       SCREAMING_SNAKE_CASE__       :			Dict													=labels
       return self.pre_processor(
           [text] * len(__lowercase )   , [F"This example is {label}" for label in labels]   , return_tensors='''pt'''   , padding='''max_length'''   , )




 def        __magic_name__		( self		:							List[Any]   , __lowercase		:							str )		->  List[Any]:
       SCREAMING_SNAKE_CASE__       :			int													=outputs.logits
       SCREAMING_SNAKE_CASE__       :			Any													=torch.argmax(logits[:, 2] ).item()
       return self._labels[label_id]