

def        __lowerCAmelCase    (       _UpperCamelCase		:  str = "The quick brown fox jumps over the lazy dog"		,							)		->							bool:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			set()

 # Replace all the whitespace in our sentence
 SCREAMING_SNAKE_CASE								=			input_str.replace(' '		,							''	)
 for alpha in input_str:
  if "a" <= alpha.lower() <= "z":
   frequency.add(alpha.lower()	)
 return len(_UpperCamelCase	) == 26


def        __lowerCAmelCase    (       _UpperCamelCase		:  str = "The quick brown fox jumps over the lazy dog"		,							)		->							bool:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE								=			[False] * 26
 for char in input_str:
  if char.islower():
   SCREAMING_SNAKE_CASE								=			True
  elif char.isupper():
   SCREAMING_SNAKE_CASE								=			True
 return all(_UpperCamelCase	)


def        __lowerCAmelCase    (       _UpperCamelCase		:  str = "The quick brown fox jumps over the lazy dog"		,							)		->							bool:
 '''simple docstring'''


 return len({char for char in input_str.lower() if char.isalpha()}	) == 26


def        __lowerCAmelCase    (       )		->							None:
 '''simple docstring'''


 from timeit import timeit

 SCREAMING_SNAKE_CASE								=			'from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'
 print(timeit('is_pangram()'		,							setup=_UpperCamelCase	)	)
 print(timeit('is_pangram_faster()'		,							setup=_UpperCamelCase	)	)
 print(timeit('is_pangram_fastest()'		,							setup=_UpperCamelCase	)	)
 # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
 # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      benchmark()




# 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]

