
"""simple docstring"""


import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 			A__	(						__lowercase ,     unittest.TestCase):


     """simple docstring"""
     snake_case__	:					List[Any]													=GPTSanJapaneseTokenizer
     snake_case__	:					Optional[Any]													=False
     snake_case__	:					Optional[int]													={'''do_clean_text''': False, '''add_prefix_space''': False}

     def 		a__						(	self:						List[Any]	)->    int:
           super().setUp()

           # fmt: off
           lowerCamelCase					:					Dict        =	["""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>""", """<|bagoftoken|>""", """<|endoftext|>"""]
           # fmt: on
           lowerCamelCase					:					Tuple        =	{"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
           lowerCamelCase					:					Tuple        =	{"""unk_token""": """<unk>"""}

           lowerCamelCase					:					List[str]        =	os.path.join(self.tmpdirname     ,		VOCAB_FILES_NAMES["""vocab_file"""]	)
           lowerCamelCase					:					Optional[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(__a	)	)

     def 		a__						(	self:						List[str]     ,		**__a:						Any	)->    str:
           kwargs.update(self.special_tokens_map	)
           return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname     ,		**__a	)

     def 		a__						(	self:						List[Any]     ,		__a:						List[str]	)->    int:
           lowerCamelCase					:					Tuple        =	"""こんにちは、世界。 \nこんばんは、㔺界。😀"""
           lowerCamelCase					:					str        =	"""こんにちは、世界。 \nこんばんは、世界。😀"""
           return input_text, output_text

     def 		a__						(	self:						Optional[int]     ,		__a:						Any	)->    str:
           lowerCamelCase					:					Optional[int]        =	self.get_input_output_texts(__a	)
           lowerCamelCase					:					Optional[Any]        =	tokenizer.encode(__a     ,		add_special_tokens=__a	)
           lowerCamelCase					:					Tuple        =	tokenizer.decode(__a     ,		clean_up_tokenization_spaces=__a	)
           return text, ids

     def 		a__						(	self:						List[str]	)->    Tuple:
           pass  # TODO add if relevant

     def 		a__						(	self:						Dict	)->    Any:
           pass  # TODO add if relevant

     def 		a__						(	self:						int	)->    Optional[Any]:
           pass  # TODO add if relevant

     def 		a__						(	self:						Optional[Any]	)->    str:
           lowerCamelCase					:					Any        =	self.get_tokenizer()

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

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

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

     def 		a__						(	self:						Dict	)->    Any:
           lowerCamelCase					:					Any        =	self.get_tokenizer()

           # Testing tokenization
           lowerCamelCase					:					List[Any]        =	"""こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"""
           lowerCamelCase					:					Union[str, Any]        =	"""こんにちは、、、、世界。こんばんは、、、、世界。"""
           lowerCamelCase					:					List[Any]        =	tokenizer.encode(__a	)
           lowerCamelCase					:					int        =	tokenizer.decode(__a	)
           self.assertEqual(__a     ,		__a	)

     @slow
     def 		a__						(	self:						int	)->    List[Any]:
           lowerCamelCase					:					Tuple        =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""	)

           # Testing tokenization
           lowerCamelCase					:					Tuple        =	"""こんにちは、世界。"""
           lowerCamelCase					:					List[str]        =	"""こんばんは、㔺界。😀"""
           lowerCamelCase					:					Optional[Any]        =	"""こんにちは、世界。こんばんは、世界。😀"""
           lowerCamelCase					:					Optional[Any]        =	tokenizer.encode(prefix_text + input_text	)
           lowerCamelCase					:					Union[str, Any]        =	tokenizer.encode(""""""     ,		prefix_text=prefix_text + input_text	)
           lowerCamelCase					:					int        =	tokenizer.encode(__a     ,		prefix_text=__a	)
           lowerCamelCase					:					str        =	tokenizer.decode(__a	)
           lowerCamelCase					:					Any        =	tokenizer.decode(__a	)
           lowerCamelCase					:					str        =	tokenizer.decode(__a	)
           self.assertEqual(__a     ,		__a	)
           self.assertEqual(__a     ,		__a	)
           self.assertEqual(__a     ,		__a	)

     @slow
     def 		a__						(	self:						Tuple	)->    Any:
           lowerCamelCase					:					List[str]        =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""	)

           # Testing tokenization
           lowerCamelCase					:					Dict        =	"""こんにちは、世界。"""
           lowerCamelCase					:					Any        =	"""こんばんは、㔺界。😀"""

           lowerCamelCase					:					List[str]        =	len(tokenizer.encode(__a	)	) - 2
           lowerCamelCase					:					int        =	len(tokenizer.encode(__a	)	) - 2

           lowerCamelCase					:					str        =	[1] + [0] * (len_prefix + len_text + 1)
           lowerCamelCase					:					int        =	[1] * (len_prefix + len_text + 1) + [0]
           lowerCamelCase					:					Dict        =	[1] + [1] * (len_prefix) + [0] * (len_text + 1)

           lowerCamelCase					:					Optional[Any]        =	tokenizer(prefix_text + input_text	).token_type_ids
           lowerCamelCase					:					Tuple        =	tokenizer(""""""     ,		prefix_text=prefix_text + input_text	).token_type_ids
           lowerCamelCase					:					Optional[int]        =	tokenizer(__a     ,		prefix_text=__a	).token_type_ids
           self.assertListEqual(__a     ,		__a	)
           self.assertListEqual(__a     ,		__a	)
           self.assertListEqual(__a     ,		__a	)

     @slow
     def 		a__						(	self:						List[str]	)->    Tuple:
           lowerCamelCase					:					Dict        =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""	)

           lowerCamelCase					:					Union[str, Any]        =	tokenizer.encode("""あンいワ"""	)
           lowerCamelCase					:					int        =	tokenizer.encode(""""""     ,		prefix_text="""あンいワ"""	)
           lowerCamelCase					:					int        =	tokenizer.encode("""いワ"""     ,		prefix_text="""あン"""	)

           self.assertEqual(tokenizer.decode(__a	)     ,		tokenizer.decode(__a	)	)
           self.assertEqual(tokenizer.decode(__a	)     ,		tokenizer.decode(__a	)	)
           self.assertNotEqual(__a     ,		__a	)
           self.assertNotEqual(__a     ,		__a	)
           self.assertEqual(x_token_a[1]     ,		x_token_a[-1]	)  # SEG token
           self.assertEqual(x_token_a[1]     ,		x_token_a[3]	)  # SEG token

     @slow
     def 		a__						(	self:						Optional[int]	)->    Tuple:
           lowerCamelCase					:					int        =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""	)

           lowerCamelCase					:					Optional[int]        =	[["""武田信玄""", """は、"""], ["""織田信長""", """の配下の、"""]]
           lowerCamelCase					:					int        =	tokenizer(__a     ,		padding=__a	)
           lowerCamelCase					:					List[str]        =	tokenizer.batch_encode_plus(__a     ,		padding=__a	)

           # fmt: off
           lowerCamelCase					:					Optional[int]        =	[[35_993, 8_640, 25_948, 35_998, 30_647, 35_675, 35_999, 35_999], [35_993, 10_382, 9_868, 35_998, 30_646, 9_459, 30_646, 35_675]]
           lowerCamelCase					:					Optional[Any]        =	[[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
           lowerCamelCase					:					Dict        =	[[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
           # fmt: on
           self.assertListEqual(x_token.input_ids     ,		__a	)
           self.assertListEqual(x_token.token_type_ids     ,		__a	)
           self.assertListEqual(x_token.attention_mask     ,		__a	)
           self.assertListEqual(x_token_a.input_ids     ,		__a	)
           self.assertListEqual(x_token_a.token_type_ids     ,		__a	)
           self.assertListEqual(x_token_a.attention_mask     ,		__a	)

     def 		a__						(	self:						Any	)->    Optional[Any]:
           # Intentionally convert some words to accommodate character fluctuations unique to Japanese
           pass







     def 		a__						(	self:						Tuple	)->    Union[str, Any]:
           # tokenizer has no padding token
           pass








"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


__lowerCamelCase      :str	    =		{}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase      :Optional[Any]	    =		['GPTSw3Tokenizer']


if TYPE_CHECKING:
    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt_swa import GPTSwaTokenizer

else:
    import sys

    __lowerCamelCase      :Tuple	    =		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




