

"""simple docstring"""


import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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


a    :str			=       """▁"""

a    :List[Any]			=       get_tests_dir("fixtures/test_sentencepiece.model")

@require_sentencepiece
@require_tokenizers
class    __a							(UpperCAmelCase__      ,		unittest.TestCase):






     '''simple docstring'''
     _SCREAMING_SNAKE_CASE  :Tuple				=       BigBirdTokenizer
     _SCREAMING_SNAKE_CASE  :List[str]				=       BigBirdTokenizerFast
     _SCREAMING_SNAKE_CASE  :Dict				=       True
     _SCREAMING_SNAKE_CASE  :List[str]				=       True

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


           """simple docstring"""


           super().setUp()

           SCREAMING_SNAKE_CASE__      :					Any											=		self.tokenizer_class(lowercase_		,			keep_accents=lowercase_     )
           tokenizer.save_pretrained(self.tmpdirname     )

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


           """simple docstring"""


           SCREAMING_SNAKE_CASE__      :					List[str]											=		'''<s>'''
           SCREAMING_SNAKE_CASE__      :					Tuple											=		1

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

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


           """simple docstring"""


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

           self.assertEqual(vocab_keys[0]		,			"""<unk>"""     )
           self.assertEqual(vocab_keys[1]		,			"""<s>"""     )
           self.assertEqual(vocab_keys[-1]		,			"""[MASK]"""     )
           self.assertEqual(len(lowercase_     )		,			1_004     )

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


           """simple docstring"""


           self.assertEqual(self.get_tokenizer().vocab_size		,			1_000     )

     def     _a	(  self     )     ->					List[Any]:


           """simple docstring"""


           if not self.test_rust_tokenizer:
                 return

           SCREAMING_SNAKE_CASE__      :					List[Any]											=		self.get_tokenizer()
           SCREAMING_SNAKE_CASE__      :					int											=		self.get_rust_tokenizer()

           SCREAMING_SNAKE_CASE__      :					Optional[Any]											=		'''I was born in 92000, and this is falsé.'''

           SCREAMING_SNAKE_CASE__      :					Optional[Any]											=		tokenizer.tokenize(lowercase_     )
           SCREAMING_SNAKE_CASE__      :					str											=		rust_tokenizer.tokenize(lowercase_     )
           self.assertListEqual(lowercase_		,			lowercase_     )

           SCREAMING_SNAKE_CASE__      :					Union[str, Any]											=		tokenizer.encode(lowercase_		,			add_special_tokens=lowercase_     )
           SCREAMING_SNAKE_CASE__      :					Tuple											=		rust_tokenizer.encode(lowercase_		,			add_special_tokens=lowercase_     )
           self.assertListEqual(lowercase_		,			lowercase_     )

           SCREAMING_SNAKE_CASE__      :					List[str]											=		self.get_rust_tokenizer()
           SCREAMING_SNAKE_CASE__      :					Optional[Any]											=		tokenizer.encode(lowercase_     )
           SCREAMING_SNAKE_CASE__      :					str											=		rust_tokenizer.encode(lowercase_     )
           self.assertListEqual(lowercase_		,			lowercase_     )

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


           """simple docstring"""


           SCREAMING_SNAKE_CASE__      :					Any											=		BigBirdTokenizer(lowercase_		,			keep_accents=lowercase_     )

           SCREAMING_SNAKE_CASE__      :					Tuple											=		tokenizer.tokenize("""This is a test"""     )
           self.assertListEqual(lowercase_		,			["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]     )

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(lowercase_     )		,			[285, 46, 10, 170, 382]		,			)

           SCREAMING_SNAKE_CASE__      :					Optional[int]											=		tokenizer.tokenize("""I was born in 92000, and this is falsé."""     )
           self.assertListEqual(
               lowercase_		,			[
                   SPIECE_UNDERLINE + """I""",
                   SPIECE_UNDERLINE + """was""",
                   SPIECE_UNDERLINE + """b""",
                   """or""",
                   """n""",
                   SPIECE_UNDERLINE + """in""",
                   SPIECE_UNDERLINE + """""",
                   """9""",
                   """2""",
                   """0""",
                   """0""",
                   """0""",
                   """,""",
                   SPIECE_UNDERLINE + """and""",
                   SPIECE_UNDERLINE + """this""",
                   SPIECE_UNDERLINE + """is""",
                   SPIECE_UNDERLINE + """f""",
                   """al""",
                   """s""",
                   """é""",
                   """.""",
               ]		,			)
           SCREAMING_SNAKE_CASE__      :					Dict											=		tokenizer.convert_tokens_to_ids(lowercase_     )
           self.assertListEqual(
               lowercase_		,			[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]		,			)

           SCREAMING_SNAKE_CASE__      :					Dict											=		tokenizer.convert_ids_to_tokens(lowercase_     )
           self.assertListEqual(
               lowercase_		,			[
                   SPIECE_UNDERLINE + """I""",
                   SPIECE_UNDERLINE + """was""",
                   SPIECE_UNDERLINE + """b""",
                   """or""",
                   """n""",
                   SPIECE_UNDERLINE + """in""",
                   SPIECE_UNDERLINE + """""",
                   """<unk>""",
                   """2""",
                   """0""",
                   """0""",
                   """0""",
                   """,""",
                   SPIECE_UNDERLINE + """and""",
                   SPIECE_UNDERLINE + """this""",
                   SPIECE_UNDERLINE + """is""",
                   SPIECE_UNDERLINE + """f""",
                   """al""",
                   """s""",
                   """<unk>""",
                   """.""",
               ]		,			)

     @cached_property
     def     _a	(  self     )     ->					List[str]:


           """simple docstring"""


           return BigBirdTokenizer.from_pretrained("""google/bigbird-roberta-base"""     )

     @slow
     def     _a	(  self     )     ->					Optional[int]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__      :					Optional[Any]											=		'''Hello World!'''
           SCREAMING_SNAKE_CASE__      :					List[Any]											=		[65, 18_536, 2_260, 101, 66]

           self.assertListEqual(lowercase_		,			self.big_tokenizer.encode(lowercase_     )     )

     @slow
     def     _a	(  self     )     ->					Optional[int]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__      :					Optional[Any]											=		(
               '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
               ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
           )
           # fmt: off
           SCREAMING_SNAKE_CASE__      :					List[str]											=		[65, 871, 419, 358, 946, 991, 2_521, 452, 358, 1_357, 387, 7_751, 3_536, 112, 985, 456, 126, 865, 938, 5_400, 5_734, 458, 1_368, 467, 786, 2_462, 5_246, 1_159, 633, 865, 4_519, 457, 582, 852, 2_557, 427, 916, 508, 405, 34_324, 497, 391, 408, 11_342, 1_244, 385, 100, 938, 985, 456, 574, 362, 12_597, 3_200, 3_129, 1_172, 66]  # noqa: E231
           # fmt: on
           self.assertListEqual(lowercase_		,			self.big_tokenizer.encode(lowercase_     )     )

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


           """simple docstring"""


           import torch

           from transformers import BigBirdConfig, BigBirdModel

           # Build sequence
           SCREAMING_SNAKE_CASE__      :					List[Any]											=		list(self.big_tokenizer.get_vocab().keys()     )[:10]
           SCREAMING_SNAKE_CASE__      :					str											=		''' '''.join(lowercase_     )
           SCREAMING_SNAKE_CASE__      :					str											=		self.big_tokenizer.encode_plus(lowercase_		,			return_tensors="""pt"""		,			return_token_type_ids=lowercase_     )
           SCREAMING_SNAKE_CASE__      :					int											=		self.big_tokenizer.batch_encode_plus(
               [sequence + """ """ + sequence]		,			return_tensors="""pt"""		,			return_token_type_ids=lowercase_     )

           SCREAMING_SNAKE_CASE__      :					Union[str, Any]											=		BigBirdConfig(attention_type="""original_full"""     )
           SCREAMING_SNAKE_CASE__      :					int											=		BigBirdModel(lowercase_     )

           assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

           with torch.no_grad():
                 model(**lowercase_     )
                 model(**lowercase_     )

     @slow
     def     _a	(  self     )     ->					int:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__      :					int											=		BigBirdTokenizer.from_pretrained("""google/bigbird-roberta-base"""     )
           SCREAMING_SNAKE_CASE__      :					List[Any]											=		tokenizer.decode(tokenizer("""Paris is the [MASK]."""     ).input_ids     )

           self.assertTrue(decoded_text == """[CLS] Paris is the[MASK].[SEP]"""     )





     @slow
     def     _a	(  self     )     ->					Tuple:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__      :					Any											=		{'''input_ids''': [[65, 39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114, 66], [65, 448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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], [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]]}  # noqa: E501
           # fmt: on

           self.tokenizer_integration_test_util(
               expected_encoding=lowercase_		,			model_name="""google/bigbird-roberta-base"""		,			revision="""215c99f1600e06f83acce68422f2035b2b5c3510"""		,			)












"""simple docstring"""






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


UpperCAmelCase_   : str   			= {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_   : Dict   			= ["""GPTNeoXTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_   : List[str]   			= [
      """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GPTNeoXForCausalLM""",
      """GPTNeoXForQuestionAnswering""",
      """GPTNeoXForSequenceClassification""",
      """GPTNeoXForTokenClassification""",
      """GPTNeoXLayer""",
      """GPTNeoXModel""",
      """GPTNeoXPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gpt_neox import (
        GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTNeoXForCausalLM,
        GPTNeoXForQuestionAnswering,
        GPTNeoXForSequenceClassification,
        GPTNeoXForTokenClassification,
        GPTNeoXLayer,
        GPTNeoXModel,
        GPTNeoXPreTrainedModel,
    )


else:
  import sys

  UpperCAmelCase_   : Tuple   			= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


