





"""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  __lowercase	(	_UpperCamelCase      ,					unittest.TestCase							):







					'''simple docstring'''




					__lowerCAmelCase     =     GPTSanJapaneseTokenizer
					__lowerCAmelCase     =     False
					__lowerCAmelCase     =     {'''do_clean_text''': False, '''add_prefix_space''': False}







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

									# fmt: off
									__a       :  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>''', '''<|bagoftoken|>''', '''<|endoftext|>''']
									# fmt: on
									__a       :  Dict					=     {'''emoji''': {'''\ud83d\ude00''': '''<|emoji1|>'''}, '''emoji_inv''': {'''<|emoji1|>''': '''\ud83d\ude00'''}}  # 😀
									__a       :  Optional[Any]					=     {'''unk_token''': '''<unk>'''}

									__a       :  Tuple					=     os.path.join(self.tmpdirname		,	VOCAB_FILES_NAMES['''vocab_file''']   )
									__a       :  Dict					=     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        _lowerCamelCase						(  self		,	**_UpperCAmelCase   ):
									kwargs.update(self.special_tokens_map   )
									return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname		,	**_UpperCAmelCase   )







					def        _lowerCamelCase						(  self		,	_UpperCAmelCase   ):
									__a       :  Any					=     '''こんにちは、世界。 \nこんばんは、㔺界。😀'''
									__a       :  Union[str, Any]					=     '''こんにちは、世界。 \nこんばんは、世界。😀'''
									return input_text, output_text







					def        _lowerCamelCase						(  self		,	_UpperCAmelCase   ):
									__a				,  __a       :  Union[str, Any]					=     self.get_input_output_texts(_UpperCAmelCase   )
									__a       :  Dict					=     tokenizer.encode(_UpperCAmelCase		,	add_special_tokens=_UpperCAmelCase   )
									__a       :  Optional[int]					=     tokenizer.decode(_UpperCAmelCase		,	clean_up_tokenization_spaces=_UpperCAmelCase   )
									return text, ids







					def        _lowerCamelCase						(  self   ):
									pass  # TODO add if relevant







					def        _lowerCamelCase						(  self   ):
									pass  # TODO add if relevant







					def        _lowerCamelCase						(  self   ):
									pass  # TODO add if relevant







					def        _lowerCamelCase						(  self   ):
									__a       :  int					=     self.get_tokenizer()

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

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

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







					def        _lowerCamelCase						(  self   ):
									__a       :  Tuple					=     self.get_tokenizer()

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







					@slow
					def        _lowerCamelCase						(  self   ):
									__a       :  Optional[Any]					=     self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese'''   )

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







					@slow
					def        _lowerCamelCase						(  self   ):
									__a       :  List[str]					=     self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese'''   )

									# Testing tokenization
									__a       :  Optional[int]					=     '''こんにちは、世界。'''
									__a       :  int					=     '''こんばんは、㔺界。😀'''

									__a       :  List[str]					=     len(tokenizer.encode(_UpperCAmelCase   )   ) - 2
									__a       :  Dict					=     len(tokenizer.encode(_UpperCAmelCase   )   ) - 2

									__a       :  List[Any]					=     [1] + [0] * (len_prefix + len_text + 1)
									__a       :  Optional[Any]					=     [1] * (len_prefix + len_text + 1) + [0]
									__a       :  List[Any]					=     [1] + [1] * (len_prefix) + [0] * (len_text + 1)

									__a       :  Dict					=     tokenizer(prefix_text + input_text   ).token_type_ids
									__a       :  str					=     tokenizer(''''''		,	prefix_text=prefix_text + input_text   ).token_type_ids
									__a       :  List[str]					=     tokenizer(_UpperCAmelCase		,	prefix_text=_UpperCAmelCase   ).token_type_ids
									self.assertListEqual(_UpperCAmelCase		,	_UpperCAmelCase   )
									self.assertListEqual(_UpperCAmelCase		,	_UpperCAmelCase   )
									self.assertListEqual(_UpperCAmelCase		,	_UpperCAmelCase   )







					@slow
					def        _lowerCamelCase						(  self   ):
									__a       :  Any					=     self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese'''   )

									__a       :  Optional[int]					=     tokenizer.encode('''あンいワ'''   )
									__a       :  Optional[int]					=     tokenizer.encode(''''''		,	prefix_text='''あンいワ'''   )
									__a       :  Optional[Any]					=     tokenizer.encode('''いワ'''		,	prefix_text='''あン'''   )

									self.assertEqual(tokenizer.decode(_UpperCAmelCase   )		,	tokenizer.decode(_UpperCAmelCase   )   )
									self.assertEqual(tokenizer.decode(_UpperCAmelCase   )		,	tokenizer.decode(_UpperCAmelCase   )   )
									self.assertNotEqual(_UpperCAmelCase		,	_UpperCAmelCase   )
									self.assertNotEqual(_UpperCAmelCase		,	_UpperCAmelCase   )
									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        _lowerCamelCase						(  self   ):
									__a       :  str					=     self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese'''   )

									__a       :  Union[str, Any]					=     [['''武田信玄''', '''は、'''], ['''織田信長''', '''の配下の、''']]
									__a       :  Dict					=     tokenizer(_UpperCAmelCase		,	padding=_UpperCAmelCase   )
									__a       :  List[str]					=     tokenizer.batch_encode_plus(_UpperCAmelCase		,	padding=_UpperCAmelCase   )

									# fmt: off
									__a       :  str					=     [[35993, 8640, 25948, 35998, 30647, 35675, 35999, 35999], [35993, 10382, 9868, 35998, 30646, 9459, 30646, 35675]]
									__a       :  Dict					=     [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
									__a       :  List[Any]					=     [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
									# fmt: on
									self.assertListEqual(x_token.input_ids		,	_UpperCAmelCase   )
									self.assertListEqual(x_token.token_type_ids		,	_UpperCAmelCase   )
									self.assertListEqual(x_token.attention_mask		,	_UpperCAmelCase   )
									self.assertListEqual(x_token_a.input_ids		,	_UpperCAmelCase   )
									self.assertListEqual(x_token_a.token_type_ids		,	_UpperCAmelCase   )
									self.assertListEqual(x_token_a.attention_mask		,	_UpperCAmelCase   )







					def        _lowerCamelCase						(  self   ):
									pass







					def        _lowerCamelCase						(  self   ):
									pass


from typing import TYPE_CHECKING

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


lowercase_									=   {
    'configuration_pix2struct': [
        'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Pix2StructConfig',
        'Pix2StructTextConfig',
        'Pix2StructVisionConfig',
    ],
    'processing_pix2struct': ['Pix2StructProcessor'],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=   ['Pix2StructImageProcessor']


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_									=   [
      'PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'Pix2StructPreTrainedModel',
      'Pix2StructForConditionalGeneration',
      'Pix2StructVisionModel',
      'Pix2StructTextModel',
  ]

if TYPE_CHECKING:
  from .configuration_pixastruct import (
      PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      PixaStructConfig,
      PixaStructTextConfig,
      PixaStructVisionConfig,
  )
  from .processing_pixastruct import PixaStructProcessor

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_pixastruct import PixaStructImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_pixastruct import (
        PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST,
        PixaStructForConditionalGeneration,
        PixaStructPreTrainedModel,
        PixaStructTextModel,
        PixaStructVisionModel,
    )

else:
  import sys

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


