




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     (     snake_case__					,    unittest.TestCase						):
   UpperCAmelCase__    :       Dict		=    GPTNeoXJapaneseTokenizer
   UpperCAmelCase__    :       List[Any]		=    False
   UpperCAmelCase__    :       int		=    {"""do_clean_text""": False, """add_prefix_space""": False}







   def lowerCamelCase		( self						:		Tuple):

        """simple docstring"""


        super().setUp()

        UpperCAmelCase_		=				[
            '''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|>''',
        ]
        UpperCAmelCase_		=				{'''emoji''': {'''\ud83d\ude00''': '''<|emoji1|>'''}, '''emoji_inv''': {'''<|emoji1|>''': '''\ud83d\ude00'''}}  # 😀
        UpperCAmelCase_		=				{'''unk_token''': '''<unk>'''}

        UpperCAmelCase_		=				os.path.join(self.tmpdirname   ,		VOCAB_FILES_NAMES['''vocab_file'''])
        UpperCAmelCase_		=				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(_A))







   def lowerCamelCase		( self						:		int   ,		**_snake_case						:		str):

        """simple docstring"""


        kwargs.update(self.special_tokens_map)
        return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname   ,		**_A)







   def lowerCamelCase		( self						:		Tuple   ,		_snake_case						:		Union[str, Any]):

        """simple docstring"""


        UpperCAmelCase_		=				'''こんにちは、世界。 \nこんばんは、㔺界。😀'''
        UpperCAmelCase_		=				'''こんにちは、世界。 \nこんばんは、世界。😀'''
        return input_text, output_text







   def lowerCamelCase		( self						:		Optional[int]   ,		_snake_case						:		Optional[int]):

        """simple docstring"""


        UpperCAmelCase_	,			UpperCAmelCase_		=				self.get_input_output_texts(_A)
        UpperCAmelCase_		=				tokenizer.encode(_A   ,		add_special_tokens=_A)
        UpperCAmelCase_		=				tokenizer.decode(_A   ,		clean_up_tokenization_spaces=_A)
        return text, ids







   def lowerCamelCase		( self						:		Union[str, Any]):

        """simple docstring"""


        pass  # TODO add if relevant







   def lowerCamelCase		( self						:		str):

        """simple docstring"""


        pass  # TODO add if relevant







   def lowerCamelCase		( self						:		List[str]):

        """simple docstring"""


        pass  # TODO add if relevant







   def lowerCamelCase		( self						:		List[str]):

        """simple docstring"""


        UpperCAmelCase_		=				self.get_tokenizer()

        # Testing tokenization
        UpperCAmelCase_		=				'''こんにちは、世界。　こんばんは、㔺界。'''
        UpperCAmelCase_		=				['''こん''', '''にちは''', '''、''', '''世界''', '''。''', '''<SP>''', '''こん''', '''ばんは''', '''、''', '''㔺界''', '''。''']
        UpperCAmelCase_		=				tokenizer.tokenize(_A)
        self.assertListEqual(_A   ,		_A)

        # Testing conversion to ids without special tokens
        UpperCAmelCase_		=				[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
        UpperCAmelCase_		=				tokenizer.convert_tokens_to_ids(_A)
        self.assertListEqual(_A   ,		_A)

        # Testing conversion to ids with special tokens
        UpperCAmelCase_		=				tokens + [tokenizer.unk_token]
        UpperCAmelCase_		=				[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
        UpperCAmelCase_		=				tokenizer.convert_tokens_to_ids(_A)
        self.assertListEqual(_A   ,		_A)







   @slow
   def lowerCamelCase		( self						:		int):

        """simple docstring"""


        UpperCAmelCase_		=				self.tokenizer_class.from_pretrained('''abeja/gpt-neox-japanese-2.7b''')

        UpperCAmelCase_		=				tokenizer.encode('''ありがとう。'''   ,		add_special_tokens=_A)
        UpperCAmelCase_		=				tokenizer.encode('''どういたしまして。'''   ,		add_special_tokens=_A)

        UpperCAmelCase_		=				tokenizer.build_inputs_with_special_tokens(_A)
        UpperCAmelCase_		=				tokenizer.build_inputs_with_special_tokens(_A   ,		_A)

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







   def lowerCamelCase		( self						:		Any):

        """simple docstring"""


        pass







   def lowerCamelCase		( self						:		List[str]):

        """simple docstring"""


        pass












from typing import TYPE_CHECKING

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


UpperCamelCase__            =     {
    """configuration_marian""": ["""MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarianConfig""", """MarianOnnxConfig"""],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""MarianTokenizer"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     [
					    """MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MarianForCausalLM""",
					    """MarianModel""",
					    """MarianMTModel""",
					    """MarianPreTrainedModel""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""TFMarianModel""", """TFMarianMTModel""", """TFMarianPreTrainedModel"""]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__            =     ["""FlaxMarianModel""", """FlaxMarianMTModel""", """FlaxMarianPreTrainedModel"""]

if TYPE_CHECKING:
					from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_marian import MarianTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_marian import (
										    MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MarianForCausalLM,
										    MarianModel,
										    MarianMTModel,
										    MarianPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
					import sys

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




