

'''simple docstring'''




import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCAmelCase         =						get_tests_dir("fixtures/test_sentencepiece_bpe.model")






class   _SCREAMING_SNAKE_CASE   (   __a		,unittest.TestCase     ):
 __SCREAMING_SNAKE_CASE					:Tuple      	=					BartphoTokenizer
 __SCREAMING_SNAKE_CASE					:int      	=					False
 __SCREAMING_SNAKE_CASE					:List[Any]      	=					True



 def 			snake_case__  (   self		:   Union[str, Any]      ):
      super().setUp()

      __magic_name__						       =    ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
      __magic_name__						       =    dict(zip(a__			,				range(len(a__      )      )      )      )
      __magic_name__						       =    {'''unk_token''': '''<unk>'''}

      __magic_name__						       =    os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES['''monolingual_vocab_file''']      )
      with open(self.monolingual_vocab_file			,				'''w'''			,				encoding='''utf-8'''      ) as fp:
           for token in vocab_tokens:
                fp.write(F'''{token} {vocab_tokens[token]}\n'''      )

      __magic_name__						       =    BartphoTokenizer(a__			,				self.monolingual_vocab_file			,				**self.special_tokens_map      )
      tokenizer.save_pretrained(self.tmpdirname      )



 def 			snake_case__  (   self		:   Any			,				**a__		:   Any      ):
      kwargs.update(self.special_tokens_map      )
      return BartphoTokenizer.from_pretrained(self.tmpdirname			,				**a__      )



 def 			snake_case__  (   self		:   Any			,				a__		:   Optional[int]      ):
      __magic_name__						       =    '''This is a là test'''
      __magic_name__						       =    '''This is a<unk><unk> test'''
      return input_text, output_text



 def 			snake_case__  (   self		:   Optional[int]      ):
      __magic_name__						       =    BartphoTokenizer(a__			,				self.monolingual_vocab_file			,				**self.special_tokens_map      )
      __magic_name__						       =    '''This is a là test'''
      __magic_name__						       =    '''▁This ▁is ▁a ▁l à ▁t est'''.split()
      __magic_name__						       =    tokenizer.tokenize(a__      )
      self.assertListEqual(a__			,				a__      )

      __magic_name__						       =    tokens + [tokenizer.unk_token]
      __magic_name__						       =    [4, 5, 6, 3, 3, 7, 8, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(a__      )			,				a__      )









'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase         =						{
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						[
          "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ClapModel",
          "ClapPreTrainedModel",
          "ClapTextModel",
          "ClapTextModelWithProjection",
          "ClapAudioModel",
          "ClapAudioModelWithProjection",
      ]
      _lowerCAmelCase         =						["ClapFeatureExtractor"]

if TYPE_CHECKING:
      from .configuration_clap import (
          CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
          ClapAudioConfig,
          ClapConfig,
          ClapTextConfig,
      )
      from .processing_clap import ClapProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_clap import ClapFeatureExtractor
            from .modeling_clap import (
                CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
                ClapAudioModel,
                ClapAudioModelWithProjection,
                ClapModel,
                ClapPreTrainedModel,
                ClapTextModel,
                ClapTextModelWithProjection,
            )


else:
      import sys

      _lowerCAmelCase         =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






