

import os

a_    :						Union[str, Any]    		=      {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}


def        __lowerCAmelCase    (       _UpperCamelCase		:  str	)		->							Dict:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			0

 SCREAMING_SNAKE_CASE								=			0
 while index < len(a__	) - 1:
  SCREAMING_SNAKE_CASE								=			SYMBOLS[numerals[index]]
  SCREAMING_SNAKE_CASE								=			SYMBOLS[numerals[index + 1]]
  if current_value < next_value:
   total_value -= current_value
  else:
   total_value += current_value
  index += 1
 total_value += SYMBOLS[numerals[index]]

 return total_value


def        __lowerCAmelCase    (       _UpperCamelCase		:  Tuple	)		->							List[Any]:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			''

 SCREAMING_SNAKE_CASE								=			num // 10_00
 numerals += m_count * "M"
 num %= 10_00

 SCREAMING_SNAKE_CASE								=			num // 1_00
 if c_count == 9:
  numerals += "CM"
  c_count -= 9
 elif c_count == 4:
  numerals += "CD"
  c_count -= 4
 if c_count >= 5:
  numerals += "D"
  c_count -= 5
 numerals += c_count * "C"
 num %= 1_00

 SCREAMING_SNAKE_CASE								=			num // 10
 if x_count == 9:
  numerals += "XC"
  x_count -= 9
 elif x_count == 4:
  numerals += "XL"
  x_count -= 4
 if x_count >= 5:
  numerals += "L"
  x_count -= 5
 numerals += x_count * "X"
 num %= 10

 if num == 9:
  numerals += "IX"
  num -= 9
 elif num == 4:
  numerals += "IV"
  num -= 4
 if num >= 5:
  numerals += "V"
  num -= 5
 numerals += num * "I"

 return numerals


def        __lowerCAmelCase    (       _UpperCamelCase		:  List[str] = "/p089_roman.txt"	)		->							Union[str, Any]:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			0

 with open(os.path.dirname(a__	) + roman_numerals_filename	) as filea:
  SCREAMING_SNAKE_CASE								=			filea.readlines()

 for line in lines:
  SCREAMING_SNAKE_CASE								=			line.strip()
  SCREAMING_SNAKE_CASE								=			parse_roman_numerals(a__	)
  SCREAMING_SNAKE_CASE								=			generate_roman_numerals(a__	)
  savings += len(a__	) - len(a__	)

 return savings


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




# 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      UpperCamelCase (     SCREAMING_SNAKE_CASE   ):
    __UpperCamelCase         ="facebook/bart-large-mnli"
    __UpperCamelCase         =(
        "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."
    )
    __UpperCamelCase         ="text_classifier"
    __UpperCamelCase         =AutoTokenizer
    __UpperCamelCase         =AutoModelForSequenceClassification

    __UpperCamelCase         =["text", ["text"]]
    __UpperCamelCase         =["text"]

    def UpperCamelCase			(			self :      Optional[Any]    ):

     """simple docstring"""






     super().setup()
     SCREAMING_SNAKE_CASE								=			self.model.config
     SCREAMING_SNAKE_CASE								=			-1
     for idx, label in config.idalabel.items():
      if label.lower().startswith('entail'    ):
       SCREAMING_SNAKE_CASE								=			int(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 UpperCamelCase			(			self :      Optional[Any]							,    snake_case__ :      List[str]							,    snake_case__ :      Dict    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			labels
     return self.pre_processor(
         [text] * len(snake_case__    )							,    [F"""This example is {label}""" for label in labels]							,    return_tensors='pt'							,    padding='max_length'							,    )




    def UpperCamelCase			(			self :      Dict							,    snake_case__ :      Dict    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			outputs.logits
     SCREAMING_SNAKE_CASE								=			torch.argmax(logits[:, 2]    ).item()
     return self._labels[label_id]

