






import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
_SCREAMING_SNAKE_CASE   =  {
    "E": 12.70,
    "T": 9.06,
    "A": 8.17,
    "O": 7.51,
    "I": 6.97,
    "N": 6.75,
    "S": 6.33,
    "H": 6.09,
    "R": 5.99,
    "D": 4.25,
    "L": 4.03,
    "C": 2.78,
    "U": 2.76,
    "M": 2.41,
    "W": 2.36,
    "F": 2.23,
    "G": 2.02,
    "Y": 1.97,
    "P": 1.93,
    "B": 1.29,
    "V": 0.98,
    "K": 0.77,
    "J": 0.15,
    "X": 0.15,
    "Q": 0.10,
    "Z": 0.07,
}
_SCREAMING_SNAKE_CASE   =  "ETAOINSHRDLCUMWFGYPBVKJXQZ"
_SCREAMING_SNAKE_CASE   =  "ABCDEFGHIJKLMNOPQRSTUVWXYZ"





def        _snake_case   (_snake_case				:       str)					->	dict[str, int]:
   _lowercase              ={letter: 0 for letter in string.ascii_uppercase}
   for letter in message.upper():
      if letter in LETTERS:
         letter_count[letter] += 1

   return letter_count





def        _snake_case   (_snake_case				:       tuple)					->	str:
   return x[0]





def        _snake_case   (_snake_case				:       str)					->	str:
   _lowercase              =get_letter_count(_snake_case)
   _lowercase              ={
       freq: [] for letter, freq in letter_to_freq.items()
   }
   for letter in LETTERS:
      freq_to_letter[letter_to_freq[letter]].append(_snake_case)

   _lowercase              ={}

   for freq in freq_to_letter:
      freq_to_letter[freq].sort(key=ETAOIN.find      ,    reverse=_snake_case)
      _lowercase              =''.join(freq_to_letter[freq])

   _lowercase              =list(freq_to_letter_str.items())
   freq_pairs.sort(key=_snake_case      ,    reverse=_snake_case)

   _lowercase              =[freq_pair[1] for freq_pair in freq_pairs]

   return "".join(_snake_case)





def        _snake_case   (_snake_case				:       str)					->	int:
   _lowercase              =get_frequency_order(_snake_case)
   _lowercase              =0
   for common_letter in ETAOIN[:6]:
      if common_letter in freq_order[:6]:
         match_score += 1

   for uncommon_letter in ETAOIN[-6:]:
      if uncommon_letter in freq_order[-6:]:
         match_score += 1

   return match_score


if __name__ == "__main__":
    import doctest

    doctest.testmod()










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 					SCREAMING_SNAKE_CASE_  (       unittest.TestCase ):
       """simple docstring"""


       def 				UpperCamelCase__						(				self	:List[str]):



          """simple docstring"""

          _lowercase              =tempfile.mkdtemp()

          _lowercase              =BlipImageProcessor()
          _lowercase              =GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model')
          _lowercase              =BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert')

          _lowercase              =InstructBlipProcessor(snake_case,      snake_case,      snake_case)

          processor.save_pretrained(self.tmpdirname)





       def 				UpperCamelCase__						(				self	:List[str],      **snake_case	:str):



          """simple docstring"""

          return AutoProcessor.from_pretrained(self.tmpdirname,      **snake_case).tokenizer





       def 				UpperCamelCase__						(				self	:Optional[Any],      **snake_case	:List[Any]):



          """simple docstring"""

          return AutoProcessor.from_pretrained(self.tmpdirname,      **snake_case).image_processor





       def 				UpperCamelCase__						(				self	:Tuple,      **snake_case	:Any):



          """simple docstring"""

          return AutoProcessor.from_pretrained(self.tmpdirname,      **snake_case).qformer_tokenizer





       def 				UpperCamelCase__						(				self	:Optional[int]):



          """simple docstring"""

          shutil.rmtree(self.tmpdirname)





       def 				UpperCamelCase__						(				self	:List[str]):



          """simple docstring"""

          _lowercase              =[np.random.randint(255,      size=(3, 30, 400),      dtype=np.uinta)]

          _lowercase              =[Image.fromarray(np.moveaxis(snake_case,      0,      -1)) for x in image_inputs]

          return image_inputs





       def 				UpperCamelCase__						(				self	:List[Any]):



          """simple docstring"""

          _lowercase              =InstructBlipProcessor(
              tokenizer=self.get_tokenizer(),      image_processor=self.get_image_processor(),      qformer_tokenizer=self.get_qformer_tokenizer(),      )
          processor.save_pretrained(self.tmpdirname)

          _lowercase              =self.get_tokenizer(bos_token='(BOS)',      eos_token='(EOS)')
          _lowercase              =self.get_image_processor(do_normalize=snake_case,      padding_value=1.0)

          _lowercase              =InstructBlipProcessor.from_pretrained(
              self.tmpdirname,      bos_token='(BOS)',      eos_token='(EOS)',      do_normalize=snake_case,      padding_value=1.0)

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

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





       def 				UpperCamelCase__						(				self	:Tuple):



          """simple docstring"""

          _lowercase              =self.get_image_processor()
          _lowercase              =self.get_tokenizer()
          _lowercase              =self.get_qformer_tokenizer()

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              =self.prepare_image_inputs()

          _lowercase              =image_processor(snake_case,      return_tensors='np')
          _lowercase              =processor(images=snake_case,      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 				UpperCamelCase__						(				self	:List[Any]):



          """simple docstring"""

          _lowercase              =self.get_image_processor()
          _lowercase              =self.get_tokenizer()
          _lowercase              =self.get_qformer_tokenizer()

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              ='lower newer'

          _lowercase              =processor(text=snake_case)

          _lowercase              =tokenizer(snake_case,      return_token_type_ids=snake_case)
          _lowercase              =qformer_tokenizer(snake_case,      return_token_type_ids=snake_case)

          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 				UpperCamelCase__						(				self	:Any):



          """simple docstring"""

          _lowercase              =self.get_image_processor()
          _lowercase              =self.get_tokenizer()
          _lowercase              =self.get_qformer_tokenizer()

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              ='lower newer'
          _lowercase              =self.prepare_image_inputs()

          _lowercase              =processor(text=snake_case,      images=snake_case)

          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(snake_case):
             processor()





       def 				UpperCamelCase__						(				self	:Dict):



          """simple docstring"""

          _lowercase              =self.get_image_processor()
          _lowercase              =self.get_tokenizer()
          _lowercase              =self.get_qformer_tokenizer()

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              =[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

          _lowercase              =processor.batch_decode(snake_case)
          _lowercase              =tokenizer.batch_decode(snake_case)

          self.assertListEqual(snake_case,      snake_case)





       def 				UpperCamelCase__						(				self	:int):



          """simple docstring"""

          _lowercase              =self.get_image_processor()
          _lowercase              =self.get_tokenizer()
          _lowercase              =self.get_qformer_tokenizer()

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              ='lower newer'
          _lowercase              =self.prepare_image_inputs()

          _lowercase              =processor(text=snake_case,      images=snake_case)

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


