




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 						__lowercase		(UpperCamelCase__					,		unittest.TestCase							):




      """simple docstring"""





      _snake_case												=						GPTSanJapaneseTokenizer
      _snake_case												=						False
      _snake_case												=						{"""do_clean_text""": False, """add_prefix_space""": False}

      def      UpperCAmelCase				(				self     )		->    Union[str, Any]:
         super().setUp()

         # fmt: off
         snake_case				:    Optional[int]           =	["""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
         snake_case				:    Dict           =	{"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
         snake_case				:    Dict           =	{"""unk_token""": """<unk>"""}

         snake_case				:    Dict           =	os.path.join(self.tmpdirname    ,				VOCAB_FILES_NAMES["""vocab_file"""]     )
         snake_case				:    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(A     )     )

      def      UpperCAmelCase				(				self    ,				**A     )		->    Union[str, Any]:
         kwargs.update(self.special_tokens_map     )
         return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname    ,				**A     )

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

      def      UpperCAmelCase				(				self    ,				A     )		->    str:
         snake_case     , snake_case				:    int           =	self.get_input_output_texts(A     )
         snake_case				:    List[Any]           =	tokenizer.encode(A    ,				add_special_tokens=A     )
         snake_case				:    Union[str, Any]           =	tokenizer.decode(A    ,				clean_up_tokenization_spaces=A     )
         return text, ids

      def      UpperCAmelCase				(				self     )		->    str:
         pass  # TODO add if relevant

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

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

      def      UpperCAmelCase				(				self     )		->    int:
         snake_case				:    List[str]           =	self.get_tokenizer()

         # Testing tokenization
         snake_case				:    Any           =	"""こんにちは、世界。　こんばんは、㔺界。"""
         snake_case				:    str           =	["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
         snake_case				:    Optional[int]           =	tokenizer.tokenize(A     )
         self.assertListEqual(A    ,				A     )

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

         # Testing conversion to ids with special tokens
         snake_case				:    int           =	tokens + [tokenizer.unk_token]
         snake_case				:    Union[str, Any]           =	[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 1_9]
         snake_case				:    Union[str, Any]           =	tokenizer.convert_tokens_to_ids(A     )
         self.assertListEqual(A    ,				A     )

      def      UpperCAmelCase				(				self     )		->    int:
         snake_case				:    List[str]           =	self.get_tokenizer()

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

      @slow
      def      UpperCAmelCase				(				self     )		->    Tuple:
         snake_case				:    Tuple           =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""     )

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

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

         # Testing tokenization
         snake_case				:    Tuple           =	"""こんにちは、世界。"""
         snake_case				:    Tuple           =	"""こんばんは、㔺界。😀"""

         snake_case				:    str           =	len(tokenizer.encode(A     )     ) - 2
         snake_case				:    Optional[Any]           =	len(tokenizer.encode(A     )     ) - 2

         snake_case				:    Optional[Any]           =	[1] + [0] * (len_prefix + len_text + 1)
         snake_case				:    Tuple           =	[1] * (len_prefix + len_text + 1) + [0]
         snake_case				:    Tuple           =	[1] + [1] * (len_prefix) + [0] * (len_text + 1)

         snake_case				:    List[Any]           =	tokenizer(prefix_text + input_text     ).token_type_ids
         snake_case				:    Dict           =	tokenizer(""""""    ,				prefix_text=prefix_text + input_text     ).token_type_ids
         snake_case				:    Optional[int]           =	tokenizer(A    ,				prefix_text=A     ).token_type_ids
         self.assertListEqual(A    ,				A     )
         self.assertListEqual(A    ,				A     )
         self.assertListEqual(A    ,				A     )

      @slow
      def      UpperCAmelCase				(				self     )		->    Union[str, Any]:
         snake_case				:    Tuple           =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""     )

         snake_case				:    Any           =	tokenizer.encode("""あンいワ"""     )
         snake_case				:    int           =	tokenizer.encode(""""""    ,				prefix_text="""あンいワ"""     )
         snake_case				:    Optional[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      UpperCAmelCase				(				self     )		->    str:
         snake_case				:    Union[str, Any]           =	self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""     )

         snake_case				:    List[Any]           =	[["""武田信玄""", """は、"""], ["""織田信長""", """の配下の、"""]]
         snake_case				:    Any           =	tokenizer(A    ,				padding=A     )
         snake_case				:    Dict           =	tokenizer.batch_encode_plus(A    ,				padding=A     )

         # fmt: off
         snake_case				:    Union[str, Any]           =	[[3_5_9_9_3, 8_6_4_0, 2_5_9_4_8, 3_5_9_9_8, 3_0_6_4_7, 3_5_6_7_5, 3_5_9_9_9, 3_5_9_9_9], [3_5_9_9_3, 1_0_3_8_2, 9_8_6_8, 3_5_9_9_8, 3_0_6_4_6, 9_4_5_9, 3_0_6_4_6, 3_5_6_7_5]]
         snake_case				:    Union[str, Any]           =	[[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
         snake_case				:    Optional[int]           =	[[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      UpperCAmelCase				(				self     )		->    Dict:
         # Intentionally convert some words to accommodate character fluctuations unique to Japanese
         pass

      def      UpperCAmelCase				(				self     )		->    int:
         # tokenizer has no padding token
         pass











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase	:	List[str]				=   {
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase	:	Optional[Any]				=   [
           'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
           'Swinv2ForImageClassification',
           'Swinv2ForMaskedImageModeling',
           'Swinv2Model',
           'Swinv2PreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_swinva import (
                  SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                  SwinvaForImageClassification,
                  SwinvaForMaskedImageModeling,
                  SwinvaModel,
                  SwinvaPreTrainedModel,
              )


else:
       import sys

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





