



"""simple docstring"""






from __future__ import annotations




def 			snake_case		(		lowerCAmelCase_  ,						lowerCAmelCase_ = None  ,						lowerCAmelCase_ = None  ,						lowerCAmelCase_ = False  ,						)						->				tuple[int, float, str]:
  _snake_case   	=      cipher_alphabet or [chr(lowerCAmelCase_	) for i in range(97  ,						123	)]

  # If the argument is None or the user provided an empty dictionary
  if not frequencies_dict:
    # Frequencies of letters in the english language (how much they show up)
    _snake_case   	=      {
        '''a''': 0.0_8497,
        '''b''': 0.0_1492,
        '''c''': 0.0_2202,
        '''d''': 0.0_4253,
        '''e''': 0.1_1162,
        '''f''': 0.0_2228,
        '''g''': 0.0_2015,
        '''h''': 0.0_6094,
        '''i''': 0.0_7546,
        '''j''': 0.0_0153,
        '''k''': 0.0_1292,
        '''l''': 0.0_4025,
        '''m''': 0.0_2406,
        '''n''': 0.0_6749,
        '''o''': 0.0_7507,
        '''p''': 0.0_1929,
        '''q''': 0.0_0095,
        '''r''': 0.0_7587,
        '''s''': 0.0_6327,
        '''t''': 0.0_9356,
        '''u''': 0.0_2758,
        '''v''': 0.0_0978,
        '''w''': 0.0_2560,
        '''x''': 0.0_0150,
        '''y''': 0.0_1994,
        '''z''': 0.0_0077,
    }
  else:
    # Custom frequencies dictionary
    _snake_case   	=      frequencies_dict

  if not case_sensitive:
    _snake_case   	=      ciphertext.lower()

  # Chi squared statistic values
  _snake_case   	=      {}

  # cycle through all of the shifts
  for shift in range(len(lowerCAmelCase_	)	):
    _snake_case   	=      ''''''

    # decrypt the message with the shift
    for letter in ciphertext:
      try:
        # Try to index the letter in the alphabet
        _snake_case   	=      (alphabet_letters.index(letter.lower()	) - shift) % len(
            lowerCAmelCase_	)
        decrypted_with_shift += (
            alphabet_letters[new_key].upper()
            if case_sensitive and letter.isupper()
            else alphabet_letters[new_key]
        )
      except ValueError:
        # Append the character if it isn't in the alphabet
        decrypted_with_shift += letter

    _snake_case   	=      0.0

    # Loop through each letter in the decoded message with the shift
    for letter in decrypted_with_shift:
      if case_sensitive:
        _snake_case   	=      letter.lower()
        if letter in frequencies:
          # Get the amount of times the letter occurs in the message
          _snake_case   	=      decrypted_with_shift.lower().count(lowerCAmelCase_	)

          # Get the excepcted amount of times the letter should appear based
          # on letter frequencies
          _snake_case   	=      frequencies[letter] * occurrences

          # Complete the chi squared statistic formula
          _snake_case   	=      ((occurrences - expected) ** 2) / expected

          # Add the margin of error to the total chi squared statistic
          chi_squared_statistic += chi_letter_value
      else:
        if letter.lower() in frequencies:
          # Get the amount of times the letter occurs in the message
          _snake_case   	=      decrypted_with_shift.count(lowerCAmelCase_	)

          # Get the excepcted amount of times the letter should appear based
          # on letter frequencies
          _snake_case   	=      frequencies[letter] * occurrences

          # Complete the chi squared statistic formula
          _snake_case   	=      ((occurrences - expected) ** 2) / expected

          # Add the margin of error to the total chi squared statistic
          chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
    _snake_case   	=      (
        chi_squared_statistic,
        decrypted_with_shift,
    )

  # Get the most likely cipher by finding the cipher with the smallest chi squared
  # statistic
  def chi_squared_statistic_values_sorting_key(lowerCAmelCase_	) -> tuple[float, str]:
    return chi_squared_statistic_values[key]

  _snake_case   	=      min(
      lowerCAmelCase_  ,						key=lowerCAmelCase_  ,						)

  # Get all the data from the most likely cipher (key, decoded message)
  (
      (
      _snake_case
  )	,     (
      _snake_case
  )	,     
  )   	=      chi_squared_statistic_values[most_likely_cipher]

  # Return the data on the most likely shift
  return (
      most_likely_cipher,
      most_likely_cipher_chi_squared_value,
      decoded_most_likely_cipher,
  )










"""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.
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):
   A__		:	str           =  '''openai/whisper-base'''
   A__		:	List[Any]           =  (
       '''This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the '''
       '''transcribed text.'''
   )
   A__		:	str           =  '''transcriber'''
   A__		:	List[Any]           =  WhisperProcessor
   A__		:	Optional[int]           =  WhisperForConditionalGeneration

   A__		:	List[str]           =  ['''audio''']
   A__		:	Optional[int]           =  ['''text''']



   def    __UpperCAmelCase    (       self    :	Tuple							,       __lowerCamelCase    :	List[Any]				):



     """simple docstring"""
     return self.pre_processor(__lowerCamelCase							,       return_tensors='''pt'''				).input_features



   def    __UpperCAmelCase    (       self    :	Optional[int]							,       __lowerCamelCase    :	List[str]				):



     """simple docstring"""
     return self.model.generate(inputs=__lowerCamelCase				)





   def    __UpperCAmelCase    (       self    :	List[str]							,       __lowerCamelCase    :	int				):



     """simple docstring"""
     return self.pre_processor.batch_decode(__lowerCamelCase							,       skip_special_tokens=__lowerCamelCase				)[0]





