


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
     from PIL import Image

     from transformers import (
         AutoProcessor,
         BertTokenizerFast,
         BlipImageProcessor,
         GPTaTokenizer,
         InstructBlipProcessor,
         PreTrainedTokenizerFast,
     )







@require_vision
class 		_snake_case  (      unittest.TestCase							):




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Optional[Any] 							=       tempfile.mkdtemp()

       a						:List[str] 							=       BlipImageProcessor()
       a						:List[Any] 							=       GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''    )
       a						:int 							=       BertTokenizerFast.from_pretrained('''hf-internal-testing/tiny-random-bert'''    )

       a						:str 							=       InstructBlipProcessor(_lowerCamelCase					,  _lowerCamelCase					,  _lowerCamelCase    )

       processor.save_pretrained(self.tmpdirname    )




 def        SCREAMING_SNAKE_CASE__				(		self					,  **_lowerCamelCase    ):
       return AutoProcessor.from_pretrained(self.tmpdirname					,  **_lowerCamelCase    ).tokenizer




 def        SCREAMING_SNAKE_CASE__				(		self					,  **_lowerCamelCase    ):
       return AutoProcessor.from_pretrained(self.tmpdirname					,  **_lowerCamelCase    ).image_processor




 def        SCREAMING_SNAKE_CASE__				(		self					,  **_lowerCamelCase    ):
       return AutoProcessor.from_pretrained(self.tmpdirname					,  **_lowerCamelCase    ).qformer_tokenizer




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       shutil.rmtree(self.tmpdirname    )




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:List[str] 							=       [np.random.randint(255					,  size=(3, 30, 400)					,  dtype=np.uinta    )]

       a						:Tuple 							=       [Image.fromarray(np.moveaxis(_lowerCamelCase					,  0					,  -1    )    ) for x in image_inputs]

       return image_inputs




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Union[str, Any] 							=       InstructBlipProcessor(
           tokenizer=self.get_tokenizer()					,  image_processor=self.get_image_processor()					,  qformer_tokenizer=self.get_qformer_tokenizer()					,  )
       processor.save_pretrained(self.tmpdirname    )

       a						:List[str] 							=       self.get_tokenizer(bos_token='''(BOS)'''					,  eos_token='''(EOS)'''    )
       a						:Tuple 							=       self.get_image_processor(do_normalize=_lowerCamelCase					,  padding_value=1.0    )

       a						:Union[str, Any] 							=       InstructBlipProcessor.from_pretrained(
           self.tmpdirname					,  bos_token='''(BOS)'''					,  eos_token='''(EOS)'''					,  do_normalize=_lowerCamelCase					,  padding_value=1.0    )

       self.assertEqual(processor.tokenizer.get_vocab()					,  tokenizer_add_kwargs.get_vocab()    )
       self.assertIsInstance(processor.tokenizer					,  _lowerCamelCase    )

       self.assertEqual(processor.image_processor.to_json_string()					,  image_processor_add_kwargs.to_json_string()    )
       self.assertIsInstance(processor.image_processor					,  _lowerCamelCase    )
       self.assertIsInstance(processor.qformer_tokenizer					,  _lowerCamelCase    )




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Tuple 							=       self.get_image_processor()
       a						:Tuple 							=       self.get_tokenizer()
       a						:Union[str, Any] 							=       self.get_qformer_tokenizer()

       a						:Optional[Any] 							=       InstructBlipProcessor(
           tokenizer=_lowerCamelCase					,  image_processor=_lowerCamelCase					,  qformer_tokenizer=_lowerCamelCase    )

       a						:Optional[int] 							=       self.prepare_image_inputs()

       a						:Optional[int] 							=       image_processor(_lowerCamelCase					,  return_tensors='''np'''    )
       a						:int 							=       processor(images=_lowerCamelCase					,  return_tensors='''np'''    )

       for key in input_feat_extract.keys():
             self.assertAlmostEqual(input_feat_extract[key].sum()					,  input_processor[key].sum()					,  delta=1e-2    )




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Dict 							=       self.get_image_processor()
       a						:Any 							=       self.get_tokenizer()
       a						:Dict 							=       self.get_qformer_tokenizer()

       a						:Optional[Any] 							=       InstructBlipProcessor(
           tokenizer=_lowerCamelCase					,  image_processor=_lowerCamelCase					,  qformer_tokenizer=_lowerCamelCase    )

       a						:str 							=       '''lower newer'''

       a						:Any 							=       processor(text=_lowerCamelCase    )

       a						:List[Any] 							=       tokenizer(_lowerCamelCase					,  return_token_type_ids=_lowerCamelCase    )
       a						:Optional[int] 							=       qformer_tokenizer(_lowerCamelCase					,  return_token_type_ids=_lowerCamelCase    )

       for key in encoded_tokens.keys():
             self.assertListEqual(encoded_tokens[key]					,  encoded_processor[key]    )

       for key in encoded_tokens_qformer.keys():
             self.assertListEqual(encoded_tokens_qformer[key]					,  encoded_processor['''qformer_''' + key]    )




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:List[Any] 							=       self.get_image_processor()
       a						:str 							=       self.get_tokenizer()
       a						:Union[str, Any] 							=       self.get_qformer_tokenizer()

       a						:Tuple 							=       InstructBlipProcessor(
           tokenizer=_lowerCamelCase					,  image_processor=_lowerCamelCase					,  qformer_tokenizer=_lowerCamelCase    )

       a						:List[Any] 							=       '''lower newer'''
       a						:Union[str, Any] 							=       self.prepare_image_inputs()

       a						:Tuple 							=       processor(text=_lowerCamelCase					,  images=_lowerCamelCase    )

       self.assertListEqual(
           list(inputs.keys()    )					,  ['''input_ids''', '''attention_mask''', '''qformer_input_ids''', '''qformer_attention_mask''', '''pixel_values''']					,  )

       # test if it raises when no input is passed
       with pytest.raises(_lowerCamelCase    ):
             processor()




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:List[str] 							=       self.get_image_processor()
       a						:Union[str, Any] 							=       self.get_tokenizer()
       a						:int 							=       self.get_qformer_tokenizer()

       a						:Optional[Any] 							=       InstructBlipProcessor(
           tokenizer=_lowerCamelCase					,  image_processor=_lowerCamelCase					,  qformer_tokenizer=_lowerCamelCase    )

       a						:Tuple 							=       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       a						:Optional[Any] 							=       processor.batch_decode(_lowerCamelCase    )
       a						:List[str] 							=       tokenizer.batch_decode(_lowerCamelCase    )

       self.assertListEqual(_lowerCamelCase					,  _lowerCamelCase    )




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       a						:Dict 							=       self.get_image_processor()
       a						:List[Any] 							=       self.get_tokenizer()
       a						:str 							=       self.get_qformer_tokenizer()

       a						:List[str] 							=       InstructBlipProcessor(
           tokenizer=_lowerCamelCase					,  image_processor=_lowerCamelCase					,  qformer_tokenizer=_lowerCamelCase    )

       a						:int 							=       '''lower newer'''
       a						:Tuple 							=       self.prepare_image_inputs()

       a						:Dict 							=       processor(text=_lowerCamelCase					,  images=_lowerCamelCase    )

       self.assertListEqual(
           list(inputs.keys()    )					,  ['''input_ids''', '''attention_mask''', '''qformer_input_ids''', '''qformer_attention_mask''', '''pixel_values''']					,  )









from __future__ import annotations
def 				__lowerCamelCase						( UpperCAmelCase_						:		str ,  UpperCAmelCase_						:		list[str] | None = None ,  UpperCAmelCase_						:		dict[str, float] | None = None ,  UpperCAmelCase_						:		bool = False ,  ):




      """simple docstring"""





      a						:str 							=       cipher_alphabet or [chr(UpperCAmelCase_						) 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)
            a						:List[Any] 							=       {
                '''a''': 0.08497,
                '''b''': 0.01492,
                '''c''': 0.02202,
                '''d''': 0.04253,
                '''e''': 0.11162,
                '''f''': 0.02228,
                '''g''': 0.02015,
                '''h''': 0.06094,
                '''i''': 0.07546,
                '''j''': 0.00153,
                '''k''': 0.01292,
                '''l''': 0.04025,
                '''m''': 0.02406,
                '''n''': 0.06749,
                '''o''': 0.07507,
                '''p''': 0.01929,
                '''q''': 0.00095,
                '''r''': 0.07587,
                '''s''': 0.06327,
                '''t''': 0.09356,
                '''u''': 0.02758,
                '''v''': 0.00978,
                '''w''': 0.02560,
                '''x''': 0.00150,
                '''y''': 0.01994,
                '''z''': 0.00077,
            }
      else:
            # Custom frequencies dictionary
            a						:Dict 							=       frequencies_dict

      if not case_sensitive:
            a						:Union[str, Any] 							=       ciphertext.lower()

      # Chi squared statistic values
      a						:dict[int, tuple[float, str]] 							=       {}

      # cycle through all of the shifts
      for shift in range(len(UpperCAmelCase_						)						):
            a						:int 							=       ''''''

            # decrypt the message with the shift
            for letter in ciphertext:
                  try:
                        # Try to index the letter in the alphabet
                        a						:Dict 							=       (alphabet_letters.index(letter.lower()						) - shift) % len(
                            UpperCAmelCase_						)
                        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

            a						:List[Any] 							=       0.0

            # Loop through each letter in the decoded message with the shift
            for letter in decrypted_with_shift:
                  if case_sensitive:
                        a						:Optional[int] 							=       letter.lower()
                        if letter in frequencies:
                              # Get the amount of times the letter occurs in the message
                              a						:List[Any] 							=       decrypted_with_shift.lower().count(UpperCAmelCase_						)

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

                              # Complete the chi squared statistic formula
                              a						:Any 							=       ((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
                              a						:int 							=       decrypted_with_shift.count(UpperCAmelCase_						)

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

                              # Complete the chi squared statistic formula
                              a						:Optional[Any] 							=       ((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
            a						:Optional[Any] 							=       (
                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(UpperCAmelCase_						:		int						) -> tuple[float, str]:
            return chi_squared_statistic_values[key]

      a						:int 							=       min(
          UpperCAmelCase_ ,  key=UpperCAmelCase_ ,  )

      # Get all the data from the most likely cipher (key, decoded message)
      (
          (
          a
      )							,				(
          a
      )							,				
      )						:Optional[int] 							=       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,
      )





