





import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class        snake_case_    (		__lowercase					,unittest.TestCase						):
  A_      							=   GPTaTokenizer
  A_      							=   GPTaTokenizerFast
  A_      							=   True
  A_      							=   {'add_prefix_space': True}
  A_      							=   False






  def 				UpperCAmelCase__						(							self			:					List[Any]      )->Optional[int]:






   '''simple docstring'''

   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   __lowerCAmelCase					:	Optional[int]      =     [
       """l""",
       """o""",
       """w""",
       """e""",
       """r""",
       """s""",
       """t""",
       """i""",
       """d""",
       """n""",
       """\u0120""",
       """\u0120l""",
       """\u0120n""",
       """\u0120lo""",
       """\u0120low""",
       """er""",
       """\u0120lowest""",
       """\u0120newer""",
       """\u0120wider""",
       """<unk>""",
       """<|endoftext|>""",
   ]
   __lowerCAmelCase					:	List[Any]      =     dict(zip(_snake_case       ,  range(len(_snake_case      )      )      )      )
   __lowerCAmelCase					:	int      =     ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
   __lowerCAmelCase					:	str      =     {"""unk_token""": """<unk>"""}

   __lowerCAmelCase					:	List[Any]      =     os.path.join(self.tmpdirname       ,  VOCAB_FILES_NAMES["""vocab_file"""]      )
   __lowerCAmelCase					:	int      =     os.path.join(self.tmpdirname       ,  VOCAB_FILES_NAMES["""merges_file"""]      )
   with open(self.vocab_file       ,  """w"""       ,  encoding="""utf-8"""      ) as fp:
    fp.write(json.dumps(_snake_case      ) + """\n"""      )
   with open(self.merges_file       ,  """w"""       ,  encoding="""utf-8"""      ) as fp:
    fp.write("""\n""".join(_snake_case      )      )






  def 				UpperCAmelCase__						(							self			:					Optional[int]       ,  **_snake_case			:					int      )->Any:






   '''simple docstring'''

   kwargs.update(self.special_tokens_map      )
   return GPTaTokenizer.from_pretrained(self.tmpdirname       ,  **_snake_case      )






  def 				UpperCAmelCase__						(							self			:					int       ,  **_snake_case			:					List[Any]      )->Tuple:






   '''simple docstring'''

   kwargs.update(self.special_tokens_map      )
   return GPTaTokenizerFast.from_pretrained(self.tmpdirname       ,  **_snake_case      )






  def 				UpperCAmelCase__						(							self			:					Optional[Any]       ,  _snake_case			:					int      )->List[Any]:






   '''simple docstring'''

   __lowerCAmelCase					:	str      =     """lower newer"""
   __lowerCAmelCase					:	Optional[int]      =     """lower newer"""
   return input_text, output_text






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->List[str]:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[int]      =     GPTaTokenizer(self.vocab_file       ,  self.merges_file       ,  **self.special_tokens_map      )
   __lowerCAmelCase					:	Dict      =     """lower newer"""
   __lowerCAmelCase					:	Union[str, Any]      =     ["""\u0120low""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
   __lowerCAmelCase					:	Optional[Any]      =     tokenizer.tokenize(_snake_case       ,  add_prefix_space=_snake_case      )
   self.assertListEqual(_snake_case       ,  _snake_case      )

   __lowerCAmelCase					:	List[str]      =     tokens + [tokenizer.unk_token]
   __lowerCAmelCase					:	Tuple      =     [14, 15, 10, 9, 3, 2, 15, 19]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case      )       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					Optional[Any]      )->str:






   '''simple docstring'''

   if not self.test_rust_tokenizer:
    return

   __lowerCAmelCase					:	List[str]      =     self.get_tokenizer()
   __lowerCAmelCase					:	Optional[int]      =     self.get_rust_tokenizer(add_prefix_space=_snake_case      )

   __lowerCAmelCase					:	str      =     """lower newer"""

   # Testing tokenization
   __lowerCAmelCase					:	Optional[int]      =     tokenizer.tokenize(_snake_case       ,  add_prefix_space=_snake_case      )
   __lowerCAmelCase					:	Dict      =     rust_tokenizer.tokenize(_snake_case      )
   self.assertListEqual(_snake_case       ,  _snake_case      )

   # Testing conversion to ids without special tokens
   __lowerCAmelCase					:	Dict      =     tokenizer.encode(_snake_case       ,  add_special_tokens=_snake_case       ,  add_prefix_space=_snake_case      )
   __lowerCAmelCase					:	int      =     rust_tokenizer.encode(_snake_case       ,  add_special_tokens=_snake_case      )
   self.assertListEqual(_snake_case       ,  _snake_case      )

   # Testing conversion to ids with special tokens
   __lowerCAmelCase					:	Optional[Any]      =     self.get_rust_tokenizer(add_prefix_space=_snake_case      )
   __lowerCAmelCase					:	Any      =     tokenizer.encode(_snake_case       ,  add_prefix_space=_snake_case      )
   __lowerCAmelCase					:	List[Any]      =     rust_tokenizer.encode(_snake_case      )
   self.assertListEqual(_snake_case       ,  _snake_case      )

   # Testing the unknown token
   __lowerCAmelCase					:	str      =     tokens + [rust_tokenizer.unk_token]
   __lowerCAmelCase					:	List[str]      =     [14, 15, 10, 9, 3, 2, 15, 19]
   self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_snake_case      )       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					int       ,  *_snake_case			:					Any       ,  **_snake_case			:					Tuple      )->Tuple:






   '''simple docstring'''

   pass






  def 				UpperCAmelCase__						(							self			:					List[str]       ,  _snake_case			:					Optional[Any]=15      )->Tuple:






   '''simple docstring'''

   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
    with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
     __lowerCAmelCase					:	Dict      =     self.rust_tokenizer_class.from_pretrained(_snake_case       ,  **_snake_case      )

     # Simple input
     __lowerCAmelCase					:	int      =     """This is a simple input"""
     __lowerCAmelCase					:	List[str]      =     ["""This is a simple input 1""", """This is a simple input 2"""]
     __lowerCAmelCase					:	int      =     ("""This is a simple input""", """This is a pair""")
     __lowerCAmelCase					:	Union[str, Any]      =     [
         ("""This is a simple input 1""", """This is a simple input 2"""),
         ("""This is a simple pair 1""", """This is a simple pair 2"""),
     ]

     # Simple input tests
     self.assertRaises(_snake_case       ,  tokenizer_r.encode       ,  _snake_case       ,  max_length=_snake_case       ,  padding="""max_length"""      )

     # Simple input
     self.assertRaises(_snake_case       ,  tokenizer_r.encode_plus       ,  _snake_case       ,  max_length=_snake_case       ,  padding="""max_length"""      )

     # Simple input
     self.assertRaises(
         _snake_case       ,  tokenizer_r.batch_encode_plus       ,  _snake_case       ,  max_length=_snake_case       ,  padding="""max_length"""       ,  )

     # Pair input
     self.assertRaises(_snake_case       ,  tokenizer_r.encode       ,  _snake_case       ,  max_length=_snake_case       ,  padding="""max_length"""      )

     # Pair input
     self.assertRaises(_snake_case       ,  tokenizer_r.encode_plus       ,  _snake_case       ,  max_length=_snake_case       ,  padding="""max_length"""      )

     # Pair input
     self.assertRaises(
         _snake_case       ,  tokenizer_r.batch_encode_plus       ,  _snake_case       ,  max_length=_snake_case       ,  padding="""max_length"""       ,  )






  def 				UpperCAmelCase__						(							self			:					Tuple      )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[int]      =     GPTaTokenizer.from_pretrained(self.tmpdirname       ,  pad_token="""<pad>"""      )

   # Simple input
   __lowerCAmelCase					:	str      =     """This is a simple input"""
   __lowerCAmelCase					:	str      =     ["""This is a simple input looooooooong""", """This is a simple input"""]
   __lowerCAmelCase					:	Optional[Any]      =     ("""This is a simple input""", """This is a pair""")
   __lowerCAmelCase					:	Any      =     [
       ("""This is a simple input loooooong""", """This is a simple input"""),
       ("""This is a simple pair loooooong""", """This is a simple pair"""),
   ]

   __lowerCAmelCase					:	Optional[int]      =     tokenizer.pad_token_id

   __lowerCAmelCase					:	str      =     tokenizer(_snake_case       ,  padding="""max_length"""       ,  max_length=30       ,  return_tensors="""np"""      )
   __lowerCAmelCase					:	str      =     tokenizer(_snake_case       ,  padding=_snake_case       ,  truncate=_snake_case       ,  return_tensors="""np"""      )
   __lowerCAmelCase					:	Dict      =     tokenizer(*_snake_case       ,  padding="""max_length"""       ,  max_length=60       ,  return_tensors="""np"""      )
   __lowerCAmelCase					:	List[str]      =     tokenizer(_snake_case       ,  padding=_snake_case       ,  truncate=_snake_case       ,  return_tensors="""np"""      )

   # s
   # test single string max_length padding
   self.assertEqual(out_s["""input_ids"""].shape[-1]       ,  30      )
   self.assertTrue(pad_token_id in out_s["""input_ids"""]      )
   self.assertTrue(0 in out_s["""attention_mask"""]      )

   # s2
   # test automatic padding
   self.assertEqual(out_sa["""input_ids"""].shape[-1]       ,  33      )
   # long slice doesn't have padding
   self.assertFalse(pad_token_id in out_sa["""input_ids"""][0]      )
   self.assertFalse(0 in out_sa["""attention_mask"""][0]      )
   # short slice does have padding
   self.assertTrue(pad_token_id in out_sa["""input_ids"""][1]      )
   self.assertTrue(0 in out_sa["""attention_mask"""][1]      )

   # p
   # test single pair max_length padding
   self.assertEqual(out_p["""input_ids"""].shape[-1]       ,  60      )
   self.assertTrue(pad_token_id in out_p["""input_ids"""]      )
   self.assertTrue(0 in out_p["""attention_mask"""]      )

   # p2
   # test automatic padding pair
   self.assertEqual(out_pa["""input_ids"""].shape[-1]       ,  52      )
   # long slice pair doesn't have padding
   self.assertFalse(pad_token_id in out_pa["""input_ids"""][0]      )
   self.assertFalse(0 in out_pa["""attention_mask"""][0]      )
   # short slice pair does have padding
   self.assertTrue(pad_token_id in out_pa["""input_ids"""][1]      )
   self.assertTrue(0 in out_pa["""attention_mask"""][1]      )






  def 				UpperCAmelCase__						(							self			:					str      )->Optional[int]:






   '''simple docstring'''

   __lowerCAmelCase					:	str      =     """$$$"""
   __lowerCAmelCase					:	Tuple      =     GPTaTokenizer.from_pretrained(self.tmpdirname       ,  bos_token=_snake_case       ,  add_bos_token=_snake_case      )

   __lowerCAmelCase					:	Tuple      =     """This is a simple input"""
   __lowerCAmelCase					:	Dict      =     ["""This is a simple input 1""", """This is a simple input 2"""]

   __lowerCAmelCase					:	List[Any]      =     tokenizer.bos_token_id

   __lowerCAmelCase					:	Union[str, Any]      =     tokenizer(_snake_case      )
   __lowerCAmelCase					:	int      =     tokenizer(_snake_case      )

   self.assertEqual(out_s.input_ids[0]       ,  _snake_case      )
   self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids      )      )

   __lowerCAmelCase					:	Tuple      =     tokenizer.decode(out_s.input_ids      )
   __lowerCAmelCase					:	Optional[Any]      =     tokenizer.batch_decode(out_sa.input_ids      )

   self.assertEqual(decode_s.split()[0]       ,  _snake_case      )
   self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )






  def 				UpperCAmelCase__						(							self			:					List[str]      )->Dict:






   '''simple docstring'''

   pass






  def 				UpperCAmelCase__						(							self			:					int      )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	Dict      =     [self.get_tokenizer(do_lower_case=_snake_case       ,  add_bos_token=_snake_case      )]
   for tokenizer in tokenizers:
    with self.subTest(F'''{tokenizer.__class__.__name__}'''      ):
     __lowerCAmelCase					:	int      =     """Encode this."""
     __lowerCAmelCase					:	List[Any]      =     """This one too please."""
     __lowerCAmelCase					:	Union[str, Any]      =     tokenizer.encode(_snake_case       ,  add_special_tokens=_snake_case      )
     encoded_sequence += tokenizer.encode(_snake_case       ,  add_special_tokens=_snake_case      )
     __lowerCAmelCase					:	int      =     tokenizer.encode_plus(
         _snake_case       ,  _snake_case       ,  add_special_tokens=_snake_case       ,  return_special_tokens_mask=_snake_case       ,  )
     __lowerCAmelCase					:	str      =     encoded_sequence_dict["""input_ids"""]
     __lowerCAmelCase					:	List[str]      =     encoded_sequence_dict["""special_tokens_mask"""]
     self.assertEqual(len(_snake_case      )       ,  len(_snake_case      )      )

     __lowerCAmelCase					:	Tuple      =     [
         (x if not special_tokens_mask[i] else None) for i, x in enumerate(_snake_case      )
     ]
     __lowerCAmelCase					:	Union[str, Any]      =     [x for x in filtered_sequence if x is not None]
     self.assertEqual(_snake_case       ,  _snake_case      )






@require_tokenizers
class        snake_case_    (		unittest.TestCase						):






  def 				UpperCAmelCase__						(							self			:					int      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =     AutoTokenizer.from_pretrained("""facebook/opt-350m"""       ,  from_slow=_snake_case      )
   __lowerCAmelCase					:	List[Any]      =     """A photo of a cat"""

   __lowerCAmelCase					:	List[str]      =     tokenizer.encode(
       _snake_case       ,  )
   self.assertEqual(_snake_case       ,  [2, 250, 1345, 9, 10, 4758]      )
   tokenizer.save_pretrained("""test_opt"""      )

   __lowerCAmelCase					:	int      =     AutoTokenizer.from_pretrained("""./test_opt"""      )
   __lowerCAmelCase					:	Any      =     tokenizer.encode(
       _snake_case       ,  )
   self.assertEqual(_snake_case       ,  [2, 250, 1345, 9, 10, 4758]      )






  def 				UpperCAmelCase__						(							self			:					int      )->Optional[int]:






   '''simple docstring'''

   __lowerCAmelCase					:	List[str]      =     AutoTokenizer.from_pretrained("""facebook/opt-350m"""       ,  use_slow=_snake_case      )
   __lowerCAmelCase					:	Optional[int]      =     """A photo of a cat"""

   __lowerCAmelCase					:	List[Any]      =     tokenizer.encode(
       _snake_case       ,  )
   # Same as above
   self.assertEqual(_snake_case       ,  [2, 250, 1345, 9, 10, 4758]      )






  @unittest.skip("""This test is failing because of a bug in the fast tokenizer"""      )
  def 				UpperCAmelCase__						(							self			:					Union[str, Any]      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[int]      =     AutoTokenizer.from_pretrained("""facebook/opt-350m"""       ,  from_slow=_snake_case      )

   __lowerCAmelCase					:	str      =     """bos"""
   __lowerCAmelCase					:	Tuple      =     tokenizer.get_vocab()["""bos"""]

   __lowerCAmelCase					:	Any      =     """A photo of a cat"""
   __lowerCAmelCase					:	Optional[int]      =     tokenizer.encode(
       _snake_case       ,  )
   # We changed the bos token
   self.assertEqual(_snake_case       ,  [31957, 250, 1345, 9, 10, 4758]      )
   tokenizer.save_pretrained("""./tok"""      )
   __lowerCAmelCase					:	Optional[int]      =     AutoTokenizer.from_pretrained("""./tok"""      )
   self.assertTrue(tokenizer.is_fast      )
   __lowerCAmelCase					:	List[str]      =     tokenizer.encode(
       _snake_case       ,  )
   self.assertEqual(_snake_case       ,  [31957, 250, 1345, 9, 10, 4758]      )






import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase             =							get_tests_dir('fixtures/test_sentencepiece_no_bos.model')






@require_sentencepiece
@require_tokenizers
class        snake_case_    (		__lowercase					,unittest.TestCase						):
  A_      							=   PegasusTokenizer
  A_      							=   PegasusTokenizerFast
  A_      							=   True
  A_      							=   True






  def 				UpperCAmelCase__						(							self			:					List[str]      )->Dict:






   '''simple docstring'''

   super().setUp()

   # We have a SentencePiece fixture for testing
   __lowerCAmelCase					:	Optional[int]      =       PegasusTokenizer(_snake_case      )
   tokenizer.save_pretrained(self.tmpdirname      )






  @cached_property
  def 				UpperCAmelCase__						(							self			:					str      )->Dict:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained("""google/pegasus-large"""      )






  def 				UpperCAmelCase__						(							self			:					Optional[Any]       ,  **_snake_case			:					Tuple      )->PegasusTokenizer:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained(self.tmpdirname       ,  **_snake_case      )






  def 				UpperCAmelCase__						(							self			:					Dict       ,  _snake_case			:					List[Any]      )->Tuple:






   '''simple docstring'''

   return ("This is a test", "This is a test")






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]      )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	Dict      =       """</s>"""
   __lowerCAmelCase					:	int      =       1

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






  def 				UpperCAmelCase__						(							self			:					int      )->Tuple:






   '''simple docstring'''

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

   self.assertEqual(vocab_keys[0]       ,  """<pad>"""      )
   self.assertEqual(vocab_keys[1]       ,  """</s>"""      )
   self.assertEqual(vocab_keys[-1]       ,  """v"""      )
   self.assertEqual(len(_snake_case      )       ,  1103      )






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->Optional[int]:






   '''simple docstring'''

   self.assertEqual(self.get_tokenizer().vocab_size       ,  1103      )






  def 				UpperCAmelCase__						(							self			:					Dict      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	Any      =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	Dict      =       self.tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	str      =       (
       """Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"""
       """ </s> <pad> <pad> <pad>"""
   )
   __lowerCAmelCase					:	str      =       rust_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   __lowerCAmelCase					:	Tuple      =       py_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->Union[str, Any]:






   '''simple docstring'''

   __lowerCAmelCase					:	List[str]      =       self._large_tokenizer
   # <mask_1> masks whole sentence while <mask_2> masks single word
   __lowerCAmelCase					:	Tuple      =       """<mask_1> To ensure a <mask_2> flow of bank resolutions."""
   __lowerCAmelCase					:	List[str]      =       [2, 413, 615, 114, 3, 1971, 113, 1679, 10710, 107, 1]
   __lowerCAmelCase					:	str      =       tokenizer([raw_input_str]       ,  return_tensors=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					List[str]      )->List[str]:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[Any]      =       self._large_tokenizer
   # The tracebacks for the following asserts are **better** without messages or self.assertEqual
   assert tokenizer.vocab_size == 96103
   assert tokenizer.pad_token_id == 0
   assert tokenizer.eos_token_id == 1
   assert tokenizer.offset == 103
   assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
   assert tokenizer.unk_token == "<unk>"
   assert tokenizer.model_max_length == 1024
   __lowerCAmelCase					:	Tuple      =       """To ensure a smooth flow of bank resolutions."""
   __lowerCAmelCase					:	Optional[Any]      =       [413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
   __lowerCAmelCase					:	int      =       tokenizer([raw_input_str]       ,  return_tensors=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )
   assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]      ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]






  @require_torch
  def 				UpperCAmelCase__						(							self			:					Any      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       ["""This is going to be way too long.""" * 150, """short example"""]
   __lowerCAmelCase					:	Union[str, Any]      =       ["""not super long but more than 5 tokens""", """tiny"""]
   __lowerCAmelCase					:	Dict      =       self._large_tokenizer(_snake_case       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )
   __lowerCAmelCase					:	Tuple      =       self._large_tokenizer(
       text_target=_snake_case       ,  max_length=5       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )

   assert batch.input_ids.shape == (2, 1024)
   assert batch.attention_mask.shape == (2, 1024)
   assert targets["input_ids"].shape == (2, 5)
   assert len(_snake_case      ) == 2  # input_ids, attention_mask.






  @slow
  def 				UpperCAmelCase__						(							self			:					Optional[Any]      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[Any]      =       {"""input_ids""": [[38979, 143, 18485, 606, 130, 26669, 87686, 121, 54189, 1129, 111, 26669, 87686, 121, 9114, 14787, 121, 13249, 158, 592, 956, 121, 14621, 31576, 143, 62613, 108, 9688, 930, 43430, 11562, 62613, 304, 108, 11443, 897, 108, 9314, 17415, 63399, 108, 11443, 7614, 18316, 118, 4284, 7148, 12430, 143, 1400, 25703, 158, 111, 4284, 7148, 11772, 143, 21297, 1064, 158, 122, 204, 3506, 1754, 1133, 14787, 1581, 115, 33224, 4482, 111, 1355, 110, 29173, 317, 50833, 108, 20147, 94665, 111, 77198, 107, 1], [110, 62613, 117, 638, 112, 1133, 121, 20098, 1355, 79050, 13872, 135, 1596, 53541, 1352, 141, 13039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 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], [139, 1235, 2799, 18289, 17780, 204, 109, 9474, 1296, 107, 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]], """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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
   # fmt: on

   self.tokenizer_integration_test_util(
       expected_encoding=_snake_case       ,  model_name="""google/bigbird-pegasus-large-arxiv"""       ,  revision="""ba85d0851d708441f91440d509690f1ab6353415"""       ,  )






@require_sentencepiece
@require_tokenizers
class        snake_case_    (		__lowercase					,unittest.TestCase						):
  A_      							=   PegasusTokenizer
  A_      							=   PegasusTokenizerFast
  A_      							=   True
  A_      							=   True






  def 				UpperCAmelCase__						(							self			:					Tuple      )->Tuple:






   '''simple docstring'''

   super().setUp()

   # We have a SentencePiece fixture for testing
   __lowerCAmelCase					:	Any      =       PegasusTokenizer(_snake_case       ,  offset=0       ,  mask_token_sent=_snake_case       ,  mask_token="""[MASK]"""      )
   tokenizer.save_pretrained(self.tmpdirname      )






  @cached_property
  def 				UpperCAmelCase__						(							self			:					Any      )->str:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained("""google/bigbird-pegasus-large-arxiv"""      )






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]       ,  **_snake_case			:					Optional[Any]      )->PegasusTokenizer:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained(self.tmpdirname       ,  **_snake_case      )






  def 				UpperCAmelCase__						(							self			:					List[str]       ,  _snake_case			:					Optional[int]      )->Union[str, Any]:






   '''simple docstring'''

   return ("This is a test", "This is a test")






  def 				UpperCAmelCase__						(							self			:					List[Any]      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	Tuple      =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	List[str]      =       self.tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	int      =       (
       """Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"""
       """ <pad> <pad> <pad>"""
   )
   __lowerCAmelCase					:	str      =       rust_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   __lowerCAmelCase					:	Tuple      =       py_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )






  @require_torch
  def 				UpperCAmelCase__						(							self			:					str      )->Optional[Any]:






   '''simple docstring'''

   __lowerCAmelCase					:	int      =       ["""This is going to be way too long.""" * 1000, """short example"""]
   __lowerCAmelCase					:	Optional[int]      =       ["""not super long but more than 5 tokens""", """tiny"""]
   __lowerCAmelCase					:	str      =       self._large_tokenizer(_snake_case       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )
   __lowerCAmelCase					:	List[Any]      =       self._large_tokenizer(
       text_target=_snake_case       ,  max_length=5       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )

   assert batch.input_ids.shape == (2, 4096)
   assert batch.attention_mask.shape == (2, 4096)
   assert targets["input_ids"].shape == (2, 5)
   assert len(_snake_case      ) == 2  # input_ids, attention_mask.






  def 				UpperCAmelCase__						(							self			:					Optional[Any]      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	Tuple      =       (
       """This is an example string that is used to test the original TF implementation against the HF"""
       """ implementation"""
   )

   __lowerCAmelCase					:	Optional[Any]      =       self._large_tokenizer(_snake_case      ).input_ids

   self.assertListEqual(
       _snake_case       ,  [182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 25016, 3137, 464, 109, 26955, 3137, 1]       ,  )