



"""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


__SCREAMING_SNAKE_CASE  :						Dict    							=      get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')


class 							lowerCamelCase_(   A__,				unittest.TestCase    ):





					'''simple docstring'''



					lowercase__   :       str										= BartphoTokenizer
					lowercase__   :       Union[str, Any]										= False
					lowercase__   :       List[Any]										= True

					def 			snake_case__      (    self   ):
									super().setUp()

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

									_lowerCamelCase        =				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"""   )

									_lowerCamelCase        =				BartphoTokenizer(lowerCamelCase__				,       self.monolingual_vocab_file				,       **self.special_tokens_map   )
									tokenizer.save_pretrained(self.tmpdirname   )

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

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				'''This is a là test'''
									_lowerCamelCase        =				'''This is a<unk><unk> test'''
									return input_text, output_text





					def 			snake_case__      (    self   ):
									_lowerCamelCase        =				BartphoTokenizer(lowerCamelCase__				,       self.monolingual_vocab_file				,       **self.special_tokens_map   )
									_lowerCamelCase        =				'''This is a là test'''
									_lowerCamelCase        =				'''▁This ▁is ▁a ▁l à ▁t est'''.split()
									_lowerCamelCase        =				tokenizer.tokenize(lowerCamelCase__   )
									self.assertListEqual(lowerCamelCase__				,       lowerCamelCase__   )

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





"""simple docstring"""
from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE  :						Optional[Any]    							=      {
    '''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''VisionEncoderDecoderOnnxConfig''']
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						str    							=      ['''VisionEncoderDecoderModel''']

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						Dict    							=      ['''TFVisionEncoderDecoderModel''']

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE  :						List[Any]    							=      ['''FlaxVisionEncoderDecoderModel''']

if TYPE_CHECKING:
			from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
			import sys

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