
'''simple docstring'''

import unittest

from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken

from ...test_tokenization_common import TokenizerTesterMixin


snake_case									=    get_tests_dir("""fixtures/test_sentencepiece_bpe_char.model""")




@require_sentencepiece
@require_tokenizers
class    lowerCAmelCase       (     UpperCamelCase_    ,  unittest.TestCase  ):
 A_				:				Tuple	=			SpeechTaTokenizer
 A_				:				List[Any]	=			False
 A_				:				Optional[Any]	=			True


 def    _A	(    self  : Union[str, Any]    ):
  '''simple docstring'''

  super().setUp()

  # We have a SentencePiece fixture for testing
  lowerCAmelCase__     :   Any     		=	SpeechTaTokenizer(a__    )

  lowerCAmelCase__     :   Optional[int]     		=	AddedToken("<mask>"			,							lstrip=a__			,							rstrip=a__    )
  lowerCAmelCase__     :   Tuple     		=	mask_token
  tokenizer.add_special_tokens({"mask_token": mask_token}    )
  tokenizer.add_tokens(["<ctc_blank>"]    )

  tokenizer.save_pretrained(self.tmpdirname    )


 def    _A	(    self  : Dict			,							a__  : str    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Optional[int]     		=	"this is a test"
  lowerCAmelCase__     :   Optional[Any]     		=	"this is a test"
  return input_text, output_text


 def    _A	(    self  : Union[str, Any]			,							a__  : Any			,							a__  : Union[str, Any]=False			,							a__  : str=20			,							a__  : Optional[Any]=5    ):
  '''simple docstring'''

  lowerCAmelCase__		,     lowerCAmelCase__     :   Tuple     		=	self.get_input_output_texts(a__    )
  lowerCAmelCase__     :   List[str]     		=	tokenizer.encode(a__			,							add_special_tokens=a__    )
  lowerCAmelCase__     :   Union[str, Any]     		=	tokenizer.decode(a__			,							clean_up_tokenization_spaces=a__    )
  return text, ids


 def    _A	(    self  : List[str]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Any     		=	"<pad>"
  lowerCAmelCase__     :   List[Any]     		=	1

  self.assertEqual(self.get_tokenizer()._convert_token_to_id(a__    )			,							a__    )
  self.assertEqual(self.get_tokenizer()._convert_id_to_token(a__    )			,							a__    )


 def    _A	(    self  : str    ):
  '''simple docstring'''

  lowerCAmelCase__     :   List[Any]     		=	list(self.get_tokenizer().get_vocab().keys()    )

  self.assertEqual(vocab_keys[0]			,							"<s>"    )
  self.assertEqual(vocab_keys[1]			,							"<pad>"    )
  self.assertEqual(vocab_keys[-4]			,							"œ"    )
  self.assertEqual(vocab_keys[-2]			,							"<mask>"    )
  self.assertEqual(vocab_keys[-1]			,							"<ctc_blank>"    )
  self.assertEqual(len(a__    )			,							81    )


 def    _A	(    self  : List[Any]    ):
  '''simple docstring'''

  self.assertEqual(self.get_tokenizer().vocab_size			,							79    )


 def    _A	(    self  : List[str]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   str     		=	self.get_tokenizers(do_lower_case=a__    )
  for tokenizer in tokenizers:
   with self.subTest(F'''{tokenizer.__class__.__name__}'''    ):
    lowerCAmelCase__     :   List[Any]     		=	tokenizer.vocab_size
    lowerCAmelCase__     :   Any     		=	len(a__    )

    self.assertNotEqual(a__			,							0    )

    # We usually have added tokens from the start in tests because our vocab fixtures are
    # smaller than the original vocabs - let's not assert this
    # self.assertEqual(vocab_size, all_size)

    lowerCAmelCase__     :   int     		=	["aaaaa bbbbbb", "cccccccccdddddddd"]
    lowerCAmelCase__     :   Tuple     		=	tokenizer.add_tokens(a__    )
    lowerCAmelCase__     :   Tuple     		=	tokenizer.vocab_size
    lowerCAmelCase__     :   str     		=	len(a__    )

    self.assertNotEqual(a__			,							0    )
    self.assertEqual(a__			,							a__    )
    self.assertEqual(a__			,							len(a__    )    )
    self.assertEqual(a__			,							all_size + len(a__    )    )

    lowerCAmelCase__     :   Optional[Any]     		=	tokenizer.encode("aaaaa bbbbbb low cccccccccdddddddd l"			,							add_special_tokens=a__    )

    self.assertGreaterEqual(len(a__    )			,							4    )
    self.assertGreater(tokens[0]			,							tokenizer.vocab_size - 1    )
    self.assertGreater(tokens[-3]			,							tokenizer.vocab_size - 1    )

    lowerCAmelCase__     :   Optional[Any]     		=	{"eos_token": ">>>>|||<||<<|<<", "pad_token": "<<<<<|||>|>>>>|>"}
    lowerCAmelCase__     :   List[Any]     		=	tokenizer.add_special_tokens(a__    )
    lowerCAmelCase__     :   List[str]     		=	tokenizer.vocab_size
    lowerCAmelCase__     :   Optional[int]     		=	len(a__    )

    self.assertNotEqual(a__			,							0    )
    self.assertEqual(a__			,							a__    )
    self.assertEqual(a__			,							len(a__    )    )
    self.assertEqual(a__			,							all_size_a + len(a__    )    )

    lowerCAmelCase__     :   Dict     		=	tokenizer.encode(
        ">>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l"			,							add_special_tokens=a__    )

    self.assertGreaterEqual(len(a__    )			,							6    )
    self.assertGreater(tokens[0]			,							tokenizer.vocab_size - 1    )
    self.assertGreater(tokens[0]			,							tokens[1]    )
    self.assertGreater(tokens[-3]			,							tokenizer.vocab_size - 1    )
    self.assertGreater(tokens[-3]			,							tokens[-4]    )
    self.assertEqual(tokens[0]			,							tokenizer.eos_token_id    )
    self.assertEqual(tokens[-3]			,							tokenizer.pad_token_id    )


 def    _A	(    self  : Any    ):
  '''simple docstring'''

  pass


 def    _A	(    self  : List[str]    ):
  '''simple docstring'''

  pass


 def    _A	(    self  : Optional[Any]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Optional[int]     		=	self.get_tokenizer()

  lowerCAmelCase__     :   int     		=	tokenizer.tokenize("This is a test"    )
  # fmt: off
  self.assertListEqual(a__			,							[SPIECE_UNDERLINE, "T", "h", "i", "s", SPIECE_UNDERLINE, "i", "s", SPIECE_UNDERLINE, "a", SPIECE_UNDERLINE, "t", "e", "s", "t"]    )
  # fmt: on

  self.assertListEqual(
      tokenizer.convert_tokens_to_ids(a__    )			,							[4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6]			,							)

  lowerCAmelCase__     :   Optional[int]     		=	tokenizer.tokenize("I was born in 92000, and this is falsé."    )
  self.assertListEqual(
      a__			,							[SPIECE_UNDERLINE, "I", SPIECE_UNDERLINE, "w", "a", "s", SPIECE_UNDERLINE, "b", "o", "r", "n", SPIECE_UNDERLINE, "i", "n", SPIECE_UNDERLINE, "92000", ",", SPIECE_UNDERLINE, "a", "n", "d", SPIECE_UNDERLINE, "t", "h", "i", "s", SPIECE_UNDERLINE, "i", "s", SPIECE_UNDERLINE, "f", "a", "l", "s", "é", "."]    )

  lowerCAmelCase__     :   Optional[Any]     		=	tokenizer.convert_tokens_to_ids(a__    )
  # fmt: off
  self.assertListEqual(a__			,							[4, 30, 4, 20, 7, 12, 4, 25, 8, 13, 9, 4, 10, 9, 4, 3, 23, 4, 7, 9, 14, 4, 6, 11, 10, 12, 4, 10, 12, 4, 19, 7, 15, 12, 73, 26]    )
  # fmt: on

  lowerCAmelCase__     :   List[str]     		=	tokenizer.convert_ids_to_tokens(a__    )
  self.assertListEqual(
      a__			,							[SPIECE_UNDERLINE, "I", SPIECE_UNDERLINE, "w", "a", "s", SPIECE_UNDERLINE, "b", "o", "r", "n", SPIECE_UNDERLINE, "i", "n", SPIECE_UNDERLINE, "<unk>", ",", SPIECE_UNDERLINE, "a", "n", "d", SPIECE_UNDERLINE, "t", "h", "i", "s", SPIECE_UNDERLINE, "i", "s", SPIECE_UNDERLINE, "f", "a", "l", "s", "é", "."]    )


 @slow
 def    _A	(    self  : Optional[int]    ):
  '''simple docstring'''

  lowerCAmelCase__     :   Optional[int]     		=	[
      "Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides "
      "general-purpose architectures (BERT, GPT, RoBERTa, XLM, DistilBert, XLNet...) for Natural "
      "Language Understanding (NLU) and Natural Language Generation (NLG) with over thirty-two pretrained "
      "models in one hundred plus languages and deep interoperability between Jax, PyTorch and TensorFlow.",
      "BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly "
      "conditioning on both left and right context in all layers.",
      "The quick brown fox jumps over the lazy dog.",
  ]

  # fmt: off
  lowerCAmelCase__     :   Tuple     		=	{
      "input_ids": [
          [4, 32, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 64, 19, 8, 13, 18, 5, 13, 15, 22, 4, 28, 9, 8, 20, 9, 4, 7, 12, 4, 24, 22, 6, 8, 13, 17, 11, 39, 6, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 7, 9, 14, 4, 24, 22, 6, 8, 13, 17, 11, 39, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 39, 25, 5, 13, 6, 63, 4, 24, 13, 8, 27, 10, 14, 5, 12, 4, 21, 5, 9, 5, 13, 7, 15, 39, 24, 16, 13, 24, 8, 12, 5, 4, 7, 13, 17, 11, 10, 6, 5, 17, 6, 16, 13, 5, 12, 4, 64, 40, 47, 54, 32, 23, 4, 53, 49, 32, 23, 4, 54, 8, 40, 47, 54, 32, 7, 23, 4, 69, 52, 43, 23, 4, 51, 10, 12, 6, 10, 15, 40, 5, 13, 6, 23, 4, 69, 52, 48, 5, 6, 26, 26, 26, 63, 4, 19, 8, 13, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 61, 9, 14, 5, 13, 12, 6, 7, 9, 14, 10, 9, 21, 4, 64, 48, 52, 61, 63, 4, 7, 9, 14, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 53, 5, 9, 5, 13, 7, 6, 10, 8, 9, 4, 64, 48, 52, 53, 63, 4, 20, 10, 6, 11, 4, 8, 27, 5, 13, 4, 6, 11, 10, 13, 6, 22, 39, 6, 20, 8, 4, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 4, 18, 8, 14, 5, 15, 12, 4, 10, 9, 4, 8, 9, 5, 4, 11, 16, 9, 14, 13, 5, 14, 4, 24, 15, 16, 12, 4, 15, 7, 9, 21, 16, 7, 21, 5, 12, 4, 7, 9, 14, 4, 14, 5, 5, 24, 4, 10, 9, 6, 5, 13, 8, 24, 5, 13, 7, 25, 10, 15, 10, 6, 22, 4, 25, 5, 6, 20, 5, 5, 9, 4, 58, 7, 37, 23, 4, 49, 22, 32, 8, 13, 17, 11, 4, 7, 9, 14, 4, 32, 5, 9, 12, 8, 13, 55, 15, 8, 20, 26, 2],
          [4, 40, 47, 54, 32, 4, 10, 12, 4, 14, 5, 12, 10, 21, 9, 5, 14, 4, 6, 8, 4, 24, 13, 5, 39, 6, 13, 7, 10, 9, 4, 14, 5, 5, 24, 4, 25, 10, 14, 10, 13, 5, 17, 6, 10, 8, 9, 7, 15, 4, 13, 5, 24, 13, 5, 12, 5, 9, 6, 7, 6, 10, 8, 9, 12, 4, 19, 13, 8, 18, 4, 16, 9, 15, 7, 25, 5, 15, 5, 14, 4, 6, 5, 37, 6, 4, 25, 22, 4, 46, 8, 10, 9, 6, 15, 22, 4, 17, 8, 9, 14, 10, 6, 10, 8, 9, 10, 9, 21, 4, 8, 9, 4, 25, 8, 6, 11, 4, 15, 5, 19, 6, 4, 7, 9, 14, 4, 13, 10, 21, 11, 6, 4, 17, 8, 9, 6, 5, 37, 6, 4, 10, 9, 4, 7, 15, 15, 4, 15, 7, 22, 5, 13, 12, 26, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
          [4, 32, 11, 5, 4, 45, 16, 10, 17, 28, 4, 25, 13, 8, 20, 9, 4, 19, 8, 37, 4, 46, 16, 18, 24, 12, 4, 8, 27, 5, 13, 4, 6, 11, 5, 4, 15, 7, 57, 22, 4, 14, 8, 21, 26, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
      ],
      "attention_mask": [
          [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
          [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
          [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
      ]
  }
  # fmt: on

  self.tokenizer_integration_test_util(
      expected_encoding=a__			,							model_name="microsoft/speecht5_asr"			,							revision="c5ef64c71905caeccde0e4462ef3f9077224c524"			,							sequences=a__			,							)







'''simple docstring'''

from math import factorial

snake_case									=    {str(digit): factorial(digit) for digit in range(10)}


def        UpperCAmelCase_ (  lowerCamelCase_			):







 """simple docstring"""


 if not isinstance(lowerCamelCase_      ,			lowerCamelCase_			):
  raise TypeError("Parameter number must be int"			)

 if number < 0:
  raise ValueError("Parameter number must be greater than or equal to 0"			)

 # Converts number in string to iterate on its digits and adds its factorial.
 return sum(DIGIT_FACTORIAL[digit] for digit in str(lowerCamelCase_			)			)


def        UpperCAmelCase_ (  lowerCamelCase_ = 6_0      ,			lowerCamelCase_ = 1_0_0_0_0_0_0			):







 """simple docstring"""


 if not isinstance(lowerCamelCase_      ,			lowerCamelCase_			) or not isinstance(lowerCamelCase_      ,			lowerCamelCase_			):
  raise TypeError("Parameters chain_length and number_limit must be int"			)

 if chain_length <= 0 or number_limit <= 0:
  raise ValueError(
      "Parameters chain_length and number_limit must be greater than 0"			)

 # the counter for the chains with the exact desired length
 lowerCAmelCase__     :   str     		=	0
 # the cached sizes of the previous chains
 lowerCAmelCase__     :   dict[int, int]     		=	{}

 for start_chain_element in range(1      ,			lowerCamelCase_			):
  # The temporary set will contain the elements of the chain
  lowerCAmelCase__     :   Any     		=	set()
  lowerCAmelCase__     :   int     		=	0

  # Stop computing the chain when you find a cached size, a repeating item or the
  # length is greater then the desired one.
  lowerCAmelCase__     :   Dict     		=	start_chain_element
  while (
      chain_element not in chain_sets_lengths
      and chain_element not in chain_set
      and chain_set_length <= chain_length
  ):
   chain_set.add(lowerCamelCase_			)
   chain_set_length += 1
   lowerCAmelCase__     :   Dict     		=	digit_factorial_sum(lowerCamelCase_			)

  if chain_element in chain_sets_lengths:
   chain_set_length += chain_sets_lengths[chain_element]

  lowerCAmelCase__     :   Optional[Any]     		=	chain_set_length

  # If chain contains the exact amount of elements increase the counter
  if chain_set_length == chain_length:
   chains_counter += 1

 return chains_counter


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(f'{solution()}')





