
'''simple docstring'''






import json
import os
import unittest

from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import (
    VOCAB_FILES_NAMES,
    GPTNeoXJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 							_snake_case     (  lowerCAmelCase_						,    unittest.TestCase ):
	"""simple docstring"""





	_UpperCamelCase							:  Optional[Any]								=		GPTNeoXJapaneseTokenizer
	_UpperCamelCase							:  Optional[Any]								=		False
	_UpperCamelCase							:  List[Any]								=		{'''do_clean_text''': False, '''add_prefix_space''': False}




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

			lowerCAmelCase_   :       Union[str, Any]    							=[
			    '''こん''',
			    '''こんに''',
			    '''にちは''',
			    '''ばんは''',
			    '''世界,㔺界''',
			    '''、''',
			    '''。''',
			    '''<BR>''',
			    '''<SP>''',
			    '''<TAB>''',
			    '''<URL>''',
			    '''<EMAIL>''',
			    '''<TEL>''',
			    '''<DATE>''',
			    '''<PRICE>''',
			    '''<BLOCK>''',
			    '''<KIGOU>''',
			    '''<U2000U2BFF>''',
			    '''<|emoji1|>''',
			    '''<unk>''',
			    '''<|startoftext|>''',
			    '''<|endoftext|>''',
			]
			lowerCAmelCase_   :       Optional[Any]    							={'''emoji''': {'''\ud83d\ude00''': '''<|emoji1|>'''}, '''emoji_inv''': {'''<|emoji1|>''': '''\ud83d\ude00'''}}  # 😀
			lowerCAmelCase_   :       Optional[int]    							={'''unk_token''': '''<unk>'''}

			lowerCAmelCase_   :       Optional[Any]    							=os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES['''vocab_file''']      )
			lowerCAmelCase_   :       List[Any]    							=os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES['''emoji_file''']      )
			with open(self.vocab_file					,						'''w'''					,						encoding='''utf-8'''      ) as vocab_writer:
					vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]      )      )
			with open(self.emoji_file					,						'''w'''      ) as emoji_writer:
					emoji_writer.write(json.dumps(UpperCamelCase_      )      )




	def 	__A      (						self				: str					,						**UpperCamelCase_				: List[str]      ):
			kwargs.update(self.special_tokens_map      )
			return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname					,						**UpperCamelCase_      )




	def 	__A      (						self				: int					,						UpperCamelCase_				: int      ):
			lowerCAmelCase_   :       str    							='''こんにちは、世界。 \nこんばんは、㔺界。😀'''
			lowerCAmelCase_   :       Any    							='''こんにちは、世界。 \nこんばんは、世界。😀'''
			return input_text, output_text




	def 	__A      (						self				: List[str]					,						UpperCamelCase_				: str      ):
			lowerCAmelCase_							,		lowerCAmelCase_   :       Any    							=self.get_input_output_texts(UpperCamelCase_      )
			lowerCAmelCase_   :       Tuple    							=tokenizer.encode(UpperCamelCase_					,						add_special_tokens=UpperCamelCase_      )
			lowerCAmelCase_   :       Any    							=tokenizer.decode(UpperCamelCase_					,						clean_up_tokenization_spaces=UpperCamelCase_      )
			return text, ids




	def 	__A      (						self				: List[str]      ):
			pass  # TODO add if relevant




	def 	__A      (						self				: List[str]      ):
			pass  # TODO add if relevant




	def 	__A      (						self				: Dict      ):
			pass  # TODO add if relevant




	def 	__A      (						self				: Dict      ):
			lowerCAmelCase_   :       Dict    							=self.get_tokenizer()

			# Testing tokenization
			lowerCAmelCase_   :       List[Any]    							='''こんにちは、世界。　こんばんは、㔺界。'''
			lowerCAmelCase_   :       Dict    							=['''こん''', '''にちは''', '''、''', '''世界''', '''。''', '''<SP>''', '''こん''', '''ばんは''', '''、''', '''㔺界''', '''。''']
			lowerCAmelCase_   :       List[str]    							=tokenizer.tokenize(UpperCamelCase_      )
			self.assertListEqual(UpperCamelCase_					,						UpperCamelCase_      )

			# Testing conversion to ids without special tokens
			lowerCAmelCase_   :       List[Any]    							=[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
			lowerCAmelCase_   :       List[Any]    							=tokenizer.convert_tokens_to_ids(UpperCamelCase_      )
			self.assertListEqual(UpperCamelCase_					,						UpperCamelCase_      )

			# Testing conversion to ids with special tokens
			lowerCAmelCase_   :       str    							=tokens + [tokenizer.unk_token]
			lowerCAmelCase_   :       int    							=[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
			lowerCAmelCase_   :       Union[str, Any]    							=tokenizer.convert_tokens_to_ids(UpperCamelCase_      )
			self.assertListEqual(UpperCamelCase_					,						UpperCamelCase_      )




	@slow
	def 	__A      (						self				: Optional[int]      ):
			lowerCAmelCase_   :       str    							=self.tokenizer_class.from_pretrained('''abeja/gpt-neox-japanese-2.7b'''      )

			lowerCAmelCase_   :       List[str]    							=tokenizer.encode('''ありがとう。'''					,						add_special_tokens=UpperCamelCase_      )
			lowerCAmelCase_   :       List[str]    							=tokenizer.encode('''どういたしまして。'''					,						add_special_tokens=UpperCamelCase_      )

			lowerCAmelCase_   :       str    							=tokenizer.build_inputs_with_special_tokens(UpperCamelCase_      )
			lowerCAmelCase_   :       Optional[Any]    							=tokenizer.build_inputs_with_special_tokens(UpperCamelCase_					,						UpperCamelCase_      )

			assert encoded_sentence == ids_a
			assert encoded_pair == ids_a + ids_a




	def 	__A      (						self				: List[Any]      ):
			# Intentionally convert some words to accommodate character fluctuations unique to Japanese
			pass





	def 	__A      (						self				: Tuple      ):
			# tokenizer has no padding token
			pass








'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowercase	=    {'''configuration_detr''': ['''DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetrConfig''', '''DetrOnnxConfig''']}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    ['''DetrFeatureExtractor''']
							__lowercase	=    ['''DetrImageProcessor''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase	=    [
							    '''DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''DetrForObjectDetection''',
							    '''DetrForSegmentation''',
							    '''DetrModel''',
							    '''DetrPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_detr import DetrFeatureExtractor
														from .image_processing_detr import DetrImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_detr import (
														    DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DetrForObjectDetection,
														    DetrForSegmentation,
														    DetrModel,
														    DetrPreTrainedModel,
														)

else:
							import sys

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






