
import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list




@require_torchaudio
@require_sentencepiece
class  lowerCamelCase__							(				unittest.TestCase):




	'''simple docstring'''




	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> Tuple:
								__UpperCamelCase	:   Dict			   =					"laion/clap-htsat-unfused"
								__UpperCamelCase	:   Optional[int]			   =					tempfile.mkdtemp()







	def    _lowerCamelCase				(					self		:str     ,   **a		:Optional[Any]						)		-> Dict:
								return RobertaTokenizer.from_pretrained(self.checkpoint     ,   **UpperCamelCase__						)







	def    _lowerCamelCase				(					self		:str     ,   **a		:List[str]						)		-> List[str]:
								return ClapFeatureExtractor.from_pretrained(self.checkpoint     ,   **UpperCamelCase__						)







	def    _lowerCamelCase				(					self		:Union[str, Any]						)		-> Union[str, Any]:
								shutil.rmtree(self.tmpdirname						)







	def    _lowerCamelCase				(					self		:int						)		-> int:
								__UpperCamelCase	:   int			   =					self.get_tokenizer()
								__UpperCamelCase	:   Optional[Any]			   =					self.get_feature_extractor()

								__UpperCamelCase	:   List[Any]			   =					ClapProcessor(tokenizer=UpperCamelCase__     ,   feature_extractor=UpperCamelCase__						)

								processor.save_pretrained(self.tmpdirname						)
								__UpperCamelCase	:   List[str]			   =					ClapProcessor.from_pretrained(self.tmpdirname						)

								self.assertEqual(processor.tokenizer.get_vocab()     ,   tokenizer.get_vocab()						)
								self.assertIsInstance(processor.tokenizer     ,   UpperCamelCase__						)

								self.assertEqual(processor.feature_extractor.to_json_string()     ,   feature_extractor.to_json_string()						)
								self.assertIsInstance(processor.feature_extractor     ,   UpperCamelCase__						)







	def    _lowerCamelCase				(					self		:Tuple						)		-> int:
								__UpperCamelCase	:   List[Any]			   =					ClapProcessor(tokenizer=self.get_tokenizer()     ,   feature_extractor=self.get_feature_extractor()						)
								processor.save_pretrained(self.tmpdirname						)

								__UpperCamelCase	:   str			   =					self.get_tokenizer(bos_token="(BOS)"     ,   eos_token="(EOS)"						)
								__UpperCamelCase	:   Tuple			   =					self.get_feature_extractor(do_normalize=UpperCamelCase__     ,   padding_value=1.0						)

								__UpperCamelCase	:   Optional[int]			   =					ClapProcessor.from_pretrained(
								    self.tmpdirname     ,   bos_token="(BOS)"     ,   eos_token="(EOS)"     ,   do_normalize=UpperCamelCase__     ,   padding_value=1.0						)

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

								self.assertEqual(processor.feature_extractor.to_json_string()     ,   feature_extractor_add_kwargs.to_json_string()						)
								self.assertIsInstance(processor.feature_extractor     ,   UpperCamelCase__						)







	def    _lowerCamelCase				(					self		:List[Any]						)		-> List[Any]:
								__UpperCamelCase	:   int			   =					self.get_feature_extractor()
								__UpperCamelCase	:   Tuple			   =					self.get_tokenizer()

								__UpperCamelCase	:   List[str]			   =					ClapProcessor(tokenizer=UpperCamelCase__     ,   feature_extractor=UpperCamelCase__						)

								__UpperCamelCase	:   Union[str, Any]			   =					floats_list((3, 1_0_0_0)						)

								__UpperCamelCase	:   List[Any]			   =					feature_extractor(UpperCamelCase__     ,   return_tensors="np"						)
								__UpperCamelCase	:   Union[str, Any]			   =					processor(audios=UpperCamelCase__     ,   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    _lowerCamelCase				(					self		:Optional[int]						)		-> List[Any]:
								__UpperCamelCase	:   int			   =					self.get_feature_extractor()
								__UpperCamelCase	:   Optional[int]			   =					self.get_tokenizer()

								__UpperCamelCase	:   Union[str, Any]			   =					ClapProcessor(tokenizer=UpperCamelCase__     ,   feature_extractor=UpperCamelCase__						)

								__UpperCamelCase	:   int			   =					"This is a test string"

								__UpperCamelCase	:   List[Any]			   =					processor(text=UpperCamelCase__						)

								__UpperCamelCase	:   Dict			   =					tokenizer(UpperCamelCase__						)

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







	def    _lowerCamelCase				(					self		:List[str]						)		-> Dict:
								__UpperCamelCase	:   Any			   =					self.get_feature_extractor()
								__UpperCamelCase	:   int			   =					self.get_tokenizer()

								__UpperCamelCase	:   Union[str, Any]			   =					ClapProcessor(tokenizer=UpperCamelCase__     ,   feature_extractor=UpperCamelCase__						)

								__UpperCamelCase	:   int			   =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

								__UpperCamelCase	:   List[str]			   =					processor.batch_decode(UpperCamelCase__						)
								__UpperCamelCase	:   Dict			   =					tokenizer.batch_decode(UpperCamelCase__						)

								self.assertListEqual(UpperCamelCase__     ,   UpperCamelCase__						)







	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> List[str]:
								__UpperCamelCase	:   List[Any]			   =					self.get_feature_extractor()
								__UpperCamelCase	:   List[str]			   =					self.get_tokenizer()

								__UpperCamelCase	:   Union[str, Any]			   =					ClapProcessor(tokenizer=UpperCamelCase__     ,   feature_extractor=UpperCamelCase__						)

								self.assertListEqual(
								    processor.model_input_names[2:]     ,   feature_extractor.model_input_names     ,   msg="`processor` and `feature_extractor` model input names do not match"     ,   )

import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
__lowerCAmelCase			:     Optional[int]           =   {
    '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,
}
__lowerCAmelCase			:     Optional[Any]           =   'ETAOINSHRDLCUMWFGYPBVKJXQZ'
__lowerCAmelCase			:     Optional[Any]           =   'ABCDEFGHIJKLMNOPQRSTUVWXYZ'

def a__    (       A_					):






  '''simple docstring'''





  __magic_name__				     =       {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 a__    (       A_					):






  '''simple docstring'''





  return x[0]

def a__    (       A_					):






  '''simple docstring'''





  __magic_name__				     =       get_letter_count(A_					)
  __magic_name__				     =       {
      freq: [] for letter, freq in letter_to_freq.items()
  }
  for letter in LETTERS:
    freq_to_letter[letter_to_freq[letter]].append(A_					)

  __magic_name__				     =       {}

  for freq in freq_to_letter:
    freq_to_letter[freq].sort(key=ETAOIN.find,     reverse=A_					)
    __magic_name__				     =       """""".join(freq_to_letter[freq]					)

  __magic_name__				     =       list(freq_to_letter_str.items()					)
  freq_pairs.sort(key=A_,     reverse=A_					)

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

  return "".join(A_					)

def a__    (       A_					):






  '''simple docstring'''





  __magic_name__				     =       get_frequency_order(A_					)
  __magic_name__				     =       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()

