





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'''

	a    :				Dict											=       GPTSanJapaneseTokenizer
	a    :				int											=       False
	a    :				Union[str, Any]											=       {'do_clean_text': False, 'add_prefix_space': False}


	def 						_UpperCAmelCase     (self )							->							List[Any]:







				'''simple docstring'''





				super().setUp()

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

				__lowercase										=							os.path.join(self.tmpdirname     ,VOCAB_FILES_NAMES['''vocab_file'''] )
				__lowercase										=							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(_lowercase ) )


	def 						_UpperCAmelCase     (self     ,**_lowerCamelCase )							->							List[str]:







				'''simple docstring'''





				kwargs.update(self.special_tokens_map )
				return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname     ,**_lowercase )


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							str:







				'''simple docstring'''





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


	def 						_UpperCAmelCase     (self     ,_lowerCamelCase )							->							Union[str, Any]:







				'''simple docstring'''





				__lowercase										=							self.get_input_output_texts(_lowercase )
				__lowercase										=							tokenizer.encode(_lowercase     ,add_special_tokens=_lowercase )
				__lowercase										=							tokenizer.decode(_lowercase     ,clean_up_tokenization_spaces=_lowercase )
				return text, ids


	def 						_UpperCAmelCase     (self )							->							Tuple:







				'''simple docstring'''





				pass  # TODO add if relevant


	def 						_UpperCAmelCase     (self )							->							int:







				'''simple docstring'''





				pass  # TODO add if relevant


	def 						_UpperCAmelCase     (self )							->							int:







				'''simple docstring'''





				pass  # TODO add if relevant


	def 						_UpperCAmelCase     (self )							->							List[str]:







				'''simple docstring'''





				__lowercase										=							self.get_tokenizer()

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

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

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


	def 						_UpperCAmelCase     (self )							->							List[str]:







				'''simple docstring'''





				__lowercase										=							self.get_tokenizer()

				# Testing tokenization
				__lowercase										=							'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
				__lowercase										=							'こんにちは、、、、世界。こんばんは、、、、世界。'
				__lowercase										=							tokenizer.encode(_lowercase )
				__lowercase										=							tokenizer.decode(_lowercase )
				self.assertEqual(_lowercase     ,_lowercase )


	@slow
	def 						_UpperCAmelCase     (self )							->							Optional[Any]:







				'''simple docstring'''





				__lowercase										=							self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese''' )

				# Testing tokenization
				__lowercase										=							'こんにちは、世界。'
				__lowercase										=							'こんばんは、㔺界。😀'
				__lowercase										=							'こんにちは、世界。こんばんは、世界。😀'
				__lowercase										=							tokenizer.encode(prefix_text + input_text )
				__lowercase										=							tokenizer.encode(''''''     ,prefix_text=prefix_text + input_text )
				__lowercase										=							tokenizer.encode(_lowercase     ,prefix_text=_lowercase )
				__lowercase										=							tokenizer.decode(_lowercase )
				__lowercase										=							tokenizer.decode(_lowercase )
				__lowercase										=							tokenizer.decode(_lowercase )
				self.assertEqual(_lowercase     ,_lowercase )
				self.assertEqual(_lowercase     ,_lowercase )
				self.assertEqual(_lowercase     ,_lowercase )


	@slow
	def 						_UpperCAmelCase     (self )							->							Union[str, Any]:







				'''simple docstring'''





				__lowercase										=							self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese''' )

				# Testing tokenization
				__lowercase										=							'こんにちは、世界。'
				__lowercase										=							'こんばんは、㔺界。😀'

				__lowercase										=							len(tokenizer.encode(_lowercase ) ) - 2
				__lowercase										=							len(tokenizer.encode(_lowercase ) ) - 2

				__lowercase										=							[1] + [0] * (len_prefix + len_text + 1)
				__lowercase										=							[1] * (len_prefix + len_text + 1) + [0]
				__lowercase										=							[1] + [1] * (len_prefix) + [0] * (len_text + 1)

				__lowercase										=							tokenizer(prefix_text + input_text ).token_type_ids
				__lowercase										=							tokenizer(''''''     ,prefix_text=prefix_text + input_text ).token_type_ids
				__lowercase										=							tokenizer(_lowercase     ,prefix_text=_lowercase ).token_type_ids
				self.assertListEqual(_lowercase     ,_lowercase )
				self.assertListEqual(_lowercase     ,_lowercase )
				self.assertListEqual(_lowercase     ,_lowercase )


	@slow
	def 						_UpperCAmelCase     (self )							->							List[str]:







				'''simple docstring'''





				__lowercase										=							self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese''' )

				__lowercase										=							tokenizer.encode('''あンいワ''' )
				__lowercase										=							tokenizer.encode(''''''     ,prefix_text='''あンいワ''' )
				__lowercase										=							tokenizer.encode('''いワ'''     ,prefix_text='''あン''' )

				self.assertEqual(tokenizer.decode(_lowercase )     ,tokenizer.decode(_lowercase ) )
				self.assertEqual(tokenizer.decode(_lowercase )     ,tokenizer.decode(_lowercase ) )
				self.assertNotEqual(_lowercase     ,_lowercase )
				self.assertNotEqual(_lowercase     ,_lowercase )
				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:







				'''simple docstring'''





				__lowercase										=							self.tokenizer_class.from_pretrained('''Tanrei/GPTSAN-japanese''' )

				__lowercase										=							[['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
				__lowercase										=							tokenizer(_lowercase     ,padding=_lowercase )
				__lowercase										=							tokenizer.batch_encode_plus(_lowercase     ,padding=_lowercase )

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


	def 						_UpperCAmelCase     (self )							->							int:







				'''simple docstring'''





				pass


	def 						_UpperCAmelCase     (self )							->							Any:







				'''simple docstring'''





				pass












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE					=    {
    '''configuration_clipseg''': [
        '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPSegConfig''',
        '''CLIPSegTextConfig''',
        '''CLIPSegVisionConfig''',
    ],
    '''processing_clipseg''': ['''CLIPSegProcessor'''],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    [
	    '''CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''CLIPSegModel''',
	    '''CLIPSegPreTrainedModel''',
	    '''CLIPSegTextModel''',
	    '''CLIPSegVisionModel''',
	    '''CLIPSegForImageSegmentation''',
	]

if TYPE_CHECKING:
	from .configuration_clipseg import (
	    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    CLIPSegConfig,
	    CLIPSegTextConfig,
	    CLIPSegVisionConfig,
	)
	from .processing_clipseg import CLIPSegProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_clipseg import (
		    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
		    CLIPSegForImageSegmentation,
		    CLIPSegModel,
		    CLIPSegPreTrainedModel,
		    CLIPSegTextModel,
		    CLIPSegVisionModel,
		)

else:
	import sys

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





