




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


_lowerCamelCase      :						List[str]							=  """▁"""

_lowerCamelCase      :						int							=  get_tests_dir("""fixtures/test_sentencepiece.model""")


@require_sentencepiece
@require_tokenizers
class 							UpperCamelCase_       (					lowercase_						,   unittest.TestCase	):

    '''simple docstring'''






    UpperCAmelCase__				    = BigBirdTokenizer
    UpperCAmelCase__				    = BigBirdTokenizerFast
    UpperCAmelCase__				    = True
    UpperCAmelCase__				    = True


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





           '''simple docstring'''

           super().setUp()

           A__ 					=       self.tokenizer_class(lowerCamelCase_   ,					keep_accents=lowerCamelCase_)
           tokenizer.save_pretrained(self.tmpdirname)


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





           '''simple docstring'''

           A__ 					=       """<s>"""
           A__ 					=       1

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


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





           '''simple docstring'''

           A__ 					=       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(lowerCamelCase_)   ,					1_004)


    def 			SCREAMING_SNAKE_CASE				(     self :      str)		->Tuple:





           '''simple docstring'''

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


    def 			SCREAMING_SNAKE_CASE				(     self :      str)		->Any:





           '''simple docstring'''

           if not self.test_rust_tokenizer:
                  return

           A__ 					=       self.get_tokenizer()
           A__ 					=       self.get_rust_tokenizer()

           A__ 					=       """I was born in 92000, and this is falsé."""

           A__ 					=       tokenizer.tokenize(lowerCamelCase_)
           A__ 					=       rust_tokenizer.tokenize(lowerCamelCase_)
           self.assertListEqual(lowerCamelCase_   ,					lowerCamelCase_)

           A__ 					=       tokenizer.encode(lowerCamelCase_   ,					add_special_tokens=lowerCamelCase_)
           A__ 					=       rust_tokenizer.encode(lowerCamelCase_   ,					add_special_tokens=lowerCamelCase_)
           self.assertListEqual(lowerCamelCase_   ,					lowerCamelCase_)

           A__ 					=       self.get_rust_tokenizer()
           A__ 					=       tokenizer.encode(lowerCamelCase_)
           A__ 					=       rust_tokenizer.encode(lowerCamelCase_)
           self.assertListEqual(lowerCamelCase_   ,					lowerCamelCase_)


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





           '''simple docstring'''

           A__ 					=       BigBirdTokenizer(lowerCamelCase_   ,					keep_accents=lowerCamelCase_)

           A__ 					=       tokenizer.tokenize('''This is a test''')
           self.assertListEqual(lowerCamelCase_   ,					['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est'''])

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

           A__ 					=       tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
           self.assertListEqual(
               lowerCamelCase_   ,					[
                   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''',
                   '''.''',
               ]   ,					)
           A__ 					=       tokenizer.convert_tokens_to_ids(lowerCamelCase_)
           self.assertListEqual(
               lowerCamelCase_   ,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]   ,					)

           A__ 					=       tokenizer.convert_ids_to_tokens(lowerCamelCase_)
           self.assertListEqual(
               lowerCamelCase_   ,					[
                   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 			SCREAMING_SNAKE_CASE				(     self :      Optional[Any])		->Optional[int]:





           '''simple docstring'''

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


    @slow
    def 			SCREAMING_SNAKE_CASE				(     self :      List[Any])		->Optional[int]:





           '''simple docstring'''

           A__ 					=       """Hello World!"""
           A__ 					=       [65, 18_536, 2_260, 101, 66]

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


    @slow
    def 			SCREAMING_SNAKE_CASE				(     self :      Dict)		->Union[str, Any]:





           '''simple docstring'''

           A__ 					=       (
               """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
           A__ 					=       [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(lowerCamelCase_   ,					self.big_tokenizer.encode(lowerCamelCase_))


    @require_torch
    @slow
    def 			SCREAMING_SNAKE_CASE				(     self :      Optional[Any])		->List[str]:





           '''simple docstring'''

           import torch

           from transformers import BigBirdConfig, BigBirdModel

           # Build sequence
           A__ 					=       list(self.big_tokenizer.get_vocab().keys())[:10]
           A__ 					=       """ """.join(lowerCamelCase_)
           A__ 					=       self.big_tokenizer.encode_plus(lowerCamelCase_   ,					return_tensors='''pt'''   ,					return_token_type_ids=lowerCamelCase_)
           A__ 					=       self.big_tokenizer.batch_encode_plus(
               [sequence + ''' ''' + sequence]   ,					return_tensors='''pt'''   ,					return_token_type_ids=lowerCamelCase_)

           A__ 					=       BigBirdConfig(attention_type='''original_full''')
           A__ 					=       BigBirdModel(lowerCamelCase_)

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

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


    @slow
    def 			SCREAMING_SNAKE_CASE				(     self :      List[str])		->int:





           '''simple docstring'''

           A__ 					=       BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base''')
           A__ 					=       tokenizer.decode(tokenizer('''Paris is the [MASK].''').input_ids)

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





    @slow
    def 			SCREAMING_SNAKE_CASE				(     self :      str)		->Union[str, Any]:





           '''simple docstring'''

           A__ 					=       {"""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=lowerCamelCase_   ,					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            =       {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCAmelCase            =       [
							    """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            =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



