from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_    					=       {
    'configuration_bigbird_pegasus': [
        'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BigBirdPegasusConfig',
        'BigBirdPegasusOnnxConfig',
    ],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_    					=       [
       'BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST',
       'BigBirdPegasusForCausalLM',
       'BigBirdPegasusForConditionalGeneration',
       'BigBirdPegasusForQuestionAnswering',
       'BigBirdPegasusForSequenceClassification',
       'BigBirdPegasusModel',
       'BigBirdPegasusPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_bigbird_pegasus import (
       BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BigBirdPegasusConfig,
       BigBirdPegasusOnnxConfig,
   )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_bigbird_pegasus import (
          BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
          BigBirdPegasusForCausalLM,
          BigBirdPegasusForConditionalGeneration,
          BigBirdPegasusForQuestionAnswering,
          BigBirdPegasusForSequenceClassification,
          BigBirdPegasusModel,
          BigBirdPegasusPreTrainedModel,
      )


else:
   import sys

   a_    					=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin





class 		_lowercase						(					snake_case_						,      unittest.TestCase       ):
 lowercase				     =   XLMTokenizer
 lowercase				     =   False

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

  """simple docstring"""





  super().setUp()

  # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
  UpperCamelCase_					:						List[Any] =					[
      'l',
      'o',
      'w',
      'e',
      'r',
      's',
      't',
      'i',
      'd',
      'n',
      'w</w>',
      'r</w>',
      't</w>',
      'lo',
      'low',
      'er</w>',
      'low</w>',
      'lowest</w>',
      'newer</w>',
      'wider</w>',
      '<unk>',
  ]
  UpperCamelCase_					:						str =					dict(zip(snake_case   ,      range(len(snake_case			)			)			)			)
  UpperCamelCase_					:						Tuple =					['l o 123', 'lo w 1456', 'e r</w> 1789', '']

  UpperCamelCase_					:						Tuple =					os.path.join(self.tmpdirname   ,      VOCAB_FILES_NAMES['vocab_file']			)
  UpperCamelCase_					:						Any =					os.path.join(self.tmpdirname   ,      VOCAB_FILES_NAMES['merges_file']			)
  with open(self.vocab_file   ,      'w'			) as fp:
   fp.write(json.dumps(snake_case			)			)
  with open(self.merges_file   ,      'w'			) as fp:
   fp.write('\n'.join(snake_case			)			)

 def 						SCREAMING_SNAKE_CASE__   ( self	:							List[Any]   ,      snake_case	:							Union[str, Any]			)   ->						int:

  """simple docstring"""





  UpperCamelCase_					:						Tuple =					'lower newer'
  UpperCamelCase_					:						Optional[int] =					'lower newer'
  return input_text, output_text

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

  """simple docstring"""





  UpperCamelCase_					:						int =					XLMTokenizer(self.vocab_file   ,      self.merges_file			)

  UpperCamelCase_					:						List[str] =					'lower'
  UpperCamelCase_					:						Optional[int] =					['low', 'er</w>']
  UpperCamelCase_					:						Optional[Any] =					tokenizer.tokenize(snake_case			)
  self.assertListEqual(snake_case   ,      snake_case			)

  UpperCamelCase_					:						List[Any] =					tokens + ['<unk>']
  UpperCamelCase_					:						int =					[1_4, 1_5, 2_0]
  self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case			)   ,      snake_case			)


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

  """simple docstring"""





  UpperCamelCase_					:						int =					XLMTokenizer.from_pretrained('xlm-mlm-en-2048'			)

  UpperCamelCase_					:						int =					tokenizer.encode('sequence builders'   ,      add_special_tokens=snake_case			)
  UpperCamelCase_					:						Optional[int] =					tokenizer.encode('multi-sequence build'   ,      add_special_tokens=snake_case			)

  UpperCamelCase_					:						Tuple =					tokenizer.build_inputs_with_special_tokens(snake_case			)
  UpperCamelCase_					:						Any =					tokenizer.build_inputs_with_special_tokens(snake_case   ,      snake_case			)

  assert encoded_sentence == [0] + text + [1]
  assert encoded_pair == [0] + text + [1] + text_a + [1]



