





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 :int     =    get_tests_dir('fixtures/test_sentencepiece_bpe.model')






class        _a(    __A	,   unittest.TestCase    ):
		lowerCamelCase__     :Union[str, Any]   				=		BartphoTokenizer
		lowerCamelCase__     :Optional[int]   				=		False
		lowerCamelCase__     :Tuple   				=		True







		def        lowercase       (    self				)      ->      Optional[Any]:


							'''simple docstring'''

							super().setUp()

							_snake_case       :					Any				       =   ["▁This", "▁is", "▁a", "▁t", "est"]
							_snake_case       :					int				       =   dict(zip(__snake_case ,						range(len(__snake_case				)				)				)				)
							_snake_case       :					int				       =   {"unk_token": "<unk>"}

							_snake_case       :					List[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"""				)

							_snake_case       :					Optional[int]				       =   BartphoTokenizer(__snake_case ,						self.monolingual_vocab_file ,						**self.special_tokens_map				)
							tokenizer.save_pretrained(self.tmpdirname				)







		def        lowercase       (    self ,						**__snake_case				)      ->      Tuple:


							'''simple docstring'''

							kwargs.update(self.special_tokens_map				)
							return BartphoTokenizer.from_pretrained(self.tmpdirname ,						**__snake_case				)







		def        lowercase       (    self ,						__snake_case				)      ->      int:


							'''simple docstring'''

							_snake_case       :					List[str]				       =   "This is a là test"
							_snake_case       :					List[Any]				       =   "This is a<unk><unk> test"
							return input_text, output_text







		def        lowercase       (    self				)      ->      int:


							'''simple docstring'''

							_snake_case       :					List[str]				       =   BartphoTokenizer(__snake_case ,						self.monolingual_vocab_file ,						**self.special_tokens_map				)
							_snake_case       :					List[Any]				       =   "This is a là test"
							_snake_case       :					str				       =   "▁This ▁is ▁a ▁l à ▁t est".split()
							_snake_case       :					Optional[Any]				       =   tokenizer.tokenize(__snake_case				)
							self.assertListEqual(__snake_case ,						__snake_case				)

							_snake_case       :					Optional[Any]				       =   tokens + [tokenizer.unk_token]
							_snake_case       :					List[str]				       =   [4, 5, 6, 3, 3, 7, 8, 3]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case				) ,						__snake_case				)






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase :str     =    {
    'configuration_nllb_moe': [
        'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'NllbMoeConfig',
    ]
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase :Optional[int]     =    [
							    'NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'NllbMoeForConditionalGeneration',
							    'NllbMoeModel',
							    'NllbMoePreTrainedModel',
							    'NllbMoeTop2Router',
							    'NllbMoeSparseMLP',
							]


if TYPE_CHECKING:
							from .configuration_nllb_moe import (
							    NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    NllbMoeConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nllb_moe import (
														    NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NllbMoeForConditionalGeneration,
														    NllbMoeModel,
														    NllbMoePreTrainedModel,
														    NllbMoeSparseMLP,
														    NllbMoeTopaRouter,
														)


else:
							import sys

							__lowerCAmelCase :int     =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)