
import os
import unittest

from transformers import ElectraTokenizerFast
from transformers.models.electra.tokenization_electra import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    ElectraTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english

@require_tokenizers
class __snake_case	(   A__      ,			unittest.TestCase  ):
				_a	:		List[Any]=       ElectraTokenizer
				_a	:		Optional[int]=       ElectraTokenizerFast
				_a	:		Optional[int]=       True
				_a	:		int=       True
				_a	:		Dict=       filter_non_english
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											super().setUp()

											lowercase							:  Tuple 			=   [
											    """[UNK]""",
											    """[CLS]""",
											    """[SEP]""",
											    """[PAD]""",
											    """[MASK]""",
											    """want""",
											    """##want""",
											    """##ed""",
											    """wa""",
											    """un""",
											    """runn""",
											    """##ing""",
											    """,""",
											    """low""",
											    """lowest""",
											]
											lowercase							:  Optional[Any] 			=   os.path.join(self.tmpdirname	,VOCAB_FILES_NAMES["""vocab_file"""]   )
											with open(self.vocab_file	,"""w"""	,encoding="""utf-8"""   ) as vocab_writer:
																		vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]   )   )
				def    _SCREAMING_SNAKE_CASE (						self	,snake_case   ):



											'''simple docstring'''







											lowercase							:  Optional[Any] 			=   """UNwant\u00E9d,running"""
											lowercase							:  Union[str, Any] 			=   """unwanted, running"""
											return input_text, output_text
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  List[Any] 			=   self.tokenizer_class(self.vocab_file   )

											lowercase							:  Union[str, Any] 			=   tokenizer.tokenize("""UNwant\u00E9d,running"""   )
											self.assertListEqual(_lowerCAmelCase	,["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]   )
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase   )	,[9, 6, 7, 12, 10, 11]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											if not self.test_rust_tokenizer:
																		return

											lowercase							:  Any 			=   self.get_tokenizer()
											lowercase							:  Any 			=   self.get_rust_tokenizer()

											lowercase							:  Optional[int] 			=   """UNwant\u00E9d,running"""

											lowercase							:  List[Any] 			=   tokenizer.tokenize(_lowerCAmelCase   )
											lowercase							:  str 			=   rust_tokenizer.tokenize(_lowerCAmelCase   )
											self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )

											lowercase							:  Optional[int] 			=   tokenizer.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )
											lowercase							:  Tuple 			=   rust_tokenizer.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )
											self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )

											lowercase							:  Optional[int] 			=   self.get_rust_tokenizer()
											lowercase							:  Dict 			=   tokenizer.encode(_lowerCAmelCase   )
											lowercase							:  int 			=   rust_tokenizer.encode(_lowerCAmelCase   )
											self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )

											# With lower casing
											lowercase							:  Any 			=   self.get_tokenizer(do_lower_case=_lowerCAmelCase   )
											lowercase							:  Dict 			=   self.get_rust_tokenizer(do_lower_case=_lowerCAmelCase   )

											lowercase							:  Optional[int] 			=   """UNwant\u00E9d,running"""

											lowercase							:  List[str] 			=   tokenizer.tokenize(_lowerCAmelCase   )
											lowercase							:  int 			=   rust_tokenizer.tokenize(_lowerCAmelCase   )
											self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )

											lowercase							:  Union[str, Any] 			=   tokenizer.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )
											lowercase							:  int 			=   rust_tokenizer.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )
											self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )

											lowercase							:  Optional[int] 			=   self.get_rust_tokenizer()
											lowercase							:  Dict 			=   tokenizer.encode(_lowerCAmelCase   )
											lowercase							:  Optional[Any] 			=   rust_tokenizer.encode(_lowerCAmelCase   )
											self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  str 			=   BasicTokenizer()

											self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz"""   )	,["""ah""", """\u535A""", """\u63A8""", """zz"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Optional[Any] 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """   )	,["""hello""", """!""", """how""", """are""", """you""", """?"""]   )
											self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""   )	,["""hello"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Dict 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase	,strip_accents=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """   )	,["""hällo""", """!""", """how""", """are""", """you""", """?"""]   )
											self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""   )	,["""h\u00E9llo"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Union[str, Any] 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase	,strip_accents=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """   )	,["""hallo""", """!""", """how""", """are""", """you""", """?"""]   )
											self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""   )	,["""hello"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Dict 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """   )	,["""hallo""", """!""", """how""", """are""", """you""", """?"""]   )
											self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""   )	,["""hello"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Any 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """   )	,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Optional[int] 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase	,strip_accents=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """   )	,["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Optional[int] 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase	,strip_accents=_lowerCAmelCase   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """   )	,["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Any 			=   BasicTokenizer(do_lower_case=_lowerCAmelCase	,never_split=["""[UNK]"""]   )

											self.assertListEqual(
											    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]"""   )	,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Optional[Any] 			=   ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

											lowercase							:  Optional[Any] 			=   {}
											for i, token in enumerate(_lowerCAmelCase   ):
																		lowercase							:  Union[str, Any] 			=   i
											lowercase							:  int 			=   WordpieceTokenizer(vocab=_lowerCAmelCase	,unk_token="""[UNK]"""   )

											self.assertListEqual(tokenizer.tokenize(""""""   )	,[]   )

											self.assertListEqual(tokenizer.tokenize("""unwanted running"""   )	,["""un""", """##want""", """##ed""", """runn""", """##ing"""]   )

											self.assertListEqual(tokenizer.tokenize("""unwantedX running"""   )	,["""[UNK]""", """runn""", """##ing"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											self.assertTrue(_is_whitespace(""" """   )   )
											self.assertTrue(_is_whitespace("""\t"""   )   )
											self.assertTrue(_is_whitespace("""\r"""   )   )
											self.assertTrue(_is_whitespace("""\n"""   )   )
											self.assertTrue(_is_whitespace("""\u00A0"""   )   )

											self.assertFalse(_is_whitespace("""A"""   )   )
											self.assertFalse(_is_whitespace("""-"""   )   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											self.assertTrue(_is_control("""\u0005"""   )   )

											self.assertFalse(_is_control("""A"""   )   )
											self.assertFalse(_is_control(""" """   )   )
											self.assertFalse(_is_control("""\t"""   )   )
											self.assertFalse(_is_control("""\r"""   )   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											self.assertTrue(_is_punctuation("""-"""   )   )
											self.assertTrue(_is_punctuation("""$"""   )   )
											self.assertTrue(_is_punctuation("""`"""   )   )
											self.assertTrue(_is_punctuation("""."""   )   )

											self.assertFalse(_is_punctuation("""A"""   )   )
											self.assertFalse(_is_punctuation(""" """   )   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Dict 			=   self.get_tokenizer()
											lowercase							:  Dict 			=   self.get_rust_tokenizer()

											# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
											self.assertListEqual([tokenizer.tokenize(_lowerCAmelCase   ) for t in ["""Test""", """\xad""", """test"""]]	,[["""[UNK]"""], [], ["""[UNK]"""]]   )

											self.assertListEqual(
											    [rust_tokenizer.tokenize(_lowerCAmelCase   ) for t in ["""Test""", """\xad""", """test"""]]	,[["""[UNK]"""], [], ["""[UNK]"""]]   )
				@slow
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Optional[int] 			=   self.tokenizer_class.from_pretrained("""google/electra-base-discriminator"""   )

											lowercase							:  Tuple 			=   tokenizer.encode("""sequence builders"""	,add_special_tokens=_lowerCAmelCase   )
											lowercase							:  Dict 			=   tokenizer.encode("""multi-sequence build"""	,add_special_tokens=_lowerCAmelCase   )

											lowercase							:  str 			=   tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase   )
											lowercase							:  Dict 			=   tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase	,_lowerCAmelCase   )

											assert encoded_sentence == [101] + text + [102]
											assert encoded_pair == [101] + text + [102] + text_a + [102]
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
																									lowercase							:  Optional[Any] 			=   self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,**_lowerCAmelCase   )

																									lowercase							:  int 			=   f"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
																									lowercase							:  Union[str, Any] 			=   tokenizer_r.encode_plus(
																									    _lowerCAmelCase	,return_attention_mask=_lowerCAmelCase	,return_token_type_ids=_lowerCAmelCase	,return_offsets_mapping=_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase	,)

																									lowercase							:  Optional[Any] 			=   tokenizer_r.do_lower_case if hasattr(_lowerCAmelCase	,"""do_lower_case"""   ) else False
																									lowercase							:  Union[str, Any] 			=   (
																									    [
																									        ((0, 0), tokenizer_r.cls_token),
																									        ((0, 1), """A"""),
																									        ((1, 2), ""","""),
																									        ((3, 5), """na"""),
																									        ((5, 6), """##ï"""),
																									        ((6, 8), """##ve"""),
																									        ((9, 15), tokenizer_r.mask_token),
																									        ((16, 21), """Allen"""),
																									        ((21, 23), """##NL"""),
																									        ((23, 24), """##P"""),
																									        ((25, 33), """sentence"""),
																									        ((33, 34), """."""),
																									        ((0, 0), tokenizer_r.sep_token),
																									    ]
																									    if not do_lower_case
																									    else [
																									        ((0, 0), tokenizer_r.cls_token),
																									        ((0, 1), """a"""),
																									        ((1, 2), ""","""),
																									        ((3, 8), """naive"""),
																									        ((9, 15), tokenizer_r.mask_token),
																									        ((16, 21), """allen"""),
																									        ((21, 23), """##nl"""),
																									        ((23, 24), """##p"""),
																									        ((25, 33), """sentence"""),
																									        ((33, 34), """."""),
																									        ((0, 0), tokenizer_r.sep_token),
																									    ]
																									)

																									self.assertEqual(
																									    [e[1] for e in expected_results]	,tokenizer_r.convert_ids_to_tokens(tokens["""input_ids"""]   )   )
																									self.assertEqual([e[0] for e in expected_results]	,tokens["""offset_mapping"""]   )
				def    _SCREAMING_SNAKE_CASE (						self   ):



											'''simple docstring'''







											lowercase							:  Any 			=   ["""的""", """人""", """有"""]
											lowercase							:  List[str] 			=   """""".join(_lowerCAmelCase   )
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
																									lowercase							:  Optional[int] 			=   True
																									lowercase							:  Union[str, Any] 			=   self.tokenizer_class.from_pretrained(_lowerCAmelCase	,**_lowerCAmelCase   )
																									lowercase							:  Union[str, Any] 			=   self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,**_lowerCAmelCase   )

																									lowercase							:  int 			=   tokenizer_p.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )
																									lowercase							:  str 			=   tokenizer_r.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )

																									lowercase							:  List[str] 			=   tokenizer_r.convert_ids_to_tokens(_lowerCAmelCase   )
																									lowercase							:  Optional[int] 			=   tokenizer_p.convert_ids_to_tokens(_lowerCAmelCase   )

																									# it is expected that each Chinese character is not preceded by "##"
																									self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )
																									self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )

																									lowercase							:  Dict 			=   False
																									lowercase							:  Dict 			=   self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase	,**_lowerCAmelCase   )
																									lowercase							:  str 			=   self.tokenizer_class.from_pretrained(_lowerCAmelCase	,**_lowerCAmelCase   )

																									lowercase							:  Optional[int] 			=   tokenizer_r.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )
																									lowercase							:  List[Any] 			=   tokenizer_p.encode(_lowerCAmelCase	,add_special_tokens=_lowerCAmelCase   )

																									lowercase							:  Union[str, Any] 			=   tokenizer_r.convert_ids_to_tokens(_lowerCAmelCase   )
																									lowercase							:  List[Any] 			=   tokenizer_p.convert_ids_to_tokens(_lowerCAmelCase   )

																									# it is expected that only the first Chinese character is not preceded by "##".
																									lowercase							:  int 			=   [
																									    f"##{token}" if idx != 0 else token for idx, token in enumerate(_lowerCAmelCase   )
																									]
																									self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )
																									self.assertListEqual(_lowerCAmelCase	,_lowerCAmelCase   )


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_keras_nlp_available,
    is_tensorflow_text_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase						:      Any							=							{
    """configuration_gpt2""": ["""GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPT2Config""", """GPT2OnnxConfig"""],
    """tokenization_gpt2""": ["""GPT2Tokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase						:      List[Any]							=							["""GPT2TokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase						:      str							=							[
      """GPT2_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GPT2DoubleHeadsModel""",
      """GPT2ForQuestionAnswering""",
      """GPT2ForSequenceClassification""",
      """GPT2ForTokenClassification""",
      """GPT2LMHeadModel""",
      """GPT2Model""",
      """GPT2PreTrainedModel""",
      """load_tf_weights_in_gpt2""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase						:      Tuple							=							[
      """TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFGPT2DoubleHeadsModel""",
      """TFGPT2ForSequenceClassification""",
      """TFGPT2LMHeadModel""",
      """TFGPT2MainLayer""",
      """TFGPT2Model""",
      """TFGPT2PreTrainedModel""",
  ]

try:
  if not is_keras_nlp_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase						:      List[str]							=							["""TFGPT2Tokenizer"""]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase						:      str							=							["""FlaxGPT2LMHeadModel""", """FlaxGPT2Model""", """FlaxGPT2PreTrainedModel"""]

if TYPE_CHECKING:
  from .configuration_gpta import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTaConfig, GPTaOnnxConfig
  from .tokenization_gpta import GPTaTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_gpta_fast import GPTaTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gpta import (
        GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTaDoubleHeadsModel,
        GPTaForQuestionAnswering,
        GPTaForSequenceClassification,
        GPTaForTokenClassification,
        GPTaLMHeadModel,
        GPTaModel,
        GPTaPreTrainedModel,
        load_tf_weights_in_gpta,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_gpta import (
        TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFGPTaDoubleHeadsModel,
        TFGPTaForSequenceClassification,
        TFGPTaLMHeadModel,
        TFGPTaMainLayer,
        TFGPTaModel,
        TFGPTaPreTrainedModel,
    )

  try:
    if not is_keras_nlp_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_gpta_tf import TFGPTaTokenizer

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_gpta import FlaxGPTaLMHeadModel, FlaxGPTaModel, FlaxGPTaPreTrainedModel

else:
  import sys

  lowercase						:      Union[str, Any]							=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
