




"""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


__A :	List[Any]       =   get_tests_dir('fixtures/test_sentencepiece_bpe.model')




class    lowerCAmelCase__							(      _UpperCamelCase	,      unittest.TestCase     ):


				"""simple docstring"""





				__UpperCAmelCase			:  List[Any]			   =   BartphoTokenizer
				__UpperCAmelCase			:  int			   =   False
				__UpperCAmelCase			:  str			   =   True



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

						__lowercase					:		List[Any]        =					["▁This", "▁is", "▁a", "▁t", "est"]
						__lowercase					:		Dict        =					dict(zip(lowercase__     , range(len(lowercase__    )    )    )    )
						__lowercase					:		Dict        =					{"unk_token": "<unk>"}

						__lowercase					:		Optional[Any]        =					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'    )

						__lowercase					:		Optional[Any]        =					BartphoTokenizer(lowercase__     , self.monolingual_vocab_file     , **self.special_tokens_map    )
						tokenizer.save_pretrained(self.tmpdirname    )



				def    snake_case     (  self       :						Any     , **lowercase__       :						List[Any]    ):
						kwargs.update(self.special_tokens_map    )
						return BartphoTokenizer.from_pretrained(self.tmpdirname     , **lowercase__    )



				def    snake_case     (  self       :						str     , lowercase__       :						Any    ):
						__lowercase					:		Any        =					"This is a là test"
						__lowercase					:		Any        =					"This is a<unk><unk> test"
						return input_text, output_text



				def    snake_case     (  self       :						Any    ):
						__lowercase					:		List[Any]        =					BartphoTokenizer(lowercase__     , self.monolingual_vocab_file     , **self.special_tokens_map    )
						__lowercase					:		int        =					"This is a là test"
						__lowercase					:		Union[str, Any]        =					"▁This ▁is ▁a ▁l à ▁t est".split()
						__lowercase					:		str        =					tokenizer.tokenize(lowercase__    )
						self.assertListEqual(lowercase__     , lowercase__    )

						__lowercase					:		str        =					tokens + [tokenizer.unk_token]
						__lowercase					:		List[str]        =					[4, 5, 6, 3, 3, 7, 8, 3]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__    )     , lowercase__    )





"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase							:   List[Any]				=				{
    "configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase							:   int				=				[
     "LILT_PRETRAINED_MODEL_ARCHIVE_LIST",
     "LiltForQuestionAnswering",
     "LiltForSequenceClassification",
     "LiltForTokenClassification",
     "LiltModel",
     "LiltPreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_lilt import (
      LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
      LiltForQuestionAnswering,
      LiltForSequenceClassification,
      LiltForTokenClassification,
      LiltModel,
      LiltPreTrainedModel,
  )

else:
 import sys

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