






import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase			:		List[Any]   				=    get_tests_dir("fixtures/test_sentencepiece.model")
@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase_       (				snake_case__     ,    unittest.TestCase					):
							UpperCamelCase_		:Optional[int]		      =    XGLMTokenizer
							UpperCamelCase_		:Tuple		      =    XGLMTokenizerFast
							UpperCamelCase_		:Tuple		      =    True
							UpperCamelCase_		:Any		      =    True




							def 						__snake_case					(   self     :   str	):
											super().setUp()

											# We have a SentencePiece fixture for testing
											lowerCAmelCase__      			=						XGLMTokenizer(SCREAMING_SNAKE_CASE_ ,							keep_accents=SCREAMING_SNAKE_CASE_	)
											tokenizer.save_pretrained(self.tmpdirname	)




							def 						__snake_case					(   self     :   Any	):
											lowerCAmelCase__      			=						'''<pad>'''
											lowerCAmelCase__      			=						1

											self.assertEqual(self.get_tokenizer()._convert_token_to_id(SCREAMING_SNAKE_CASE_	) ,							SCREAMING_SNAKE_CASE_	)
											self.assertEqual(self.get_tokenizer()._convert_id_to_token(SCREAMING_SNAKE_CASE_	) ,							SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   List[str]	):
											lowerCAmelCase__      			=						list(self.get_tokenizer().get_vocab().keys()	)

											self.assertEqual(vocab_keys[0] ,							'''<s>'''	)
											self.assertEqual(vocab_keys[1] ,							'''<pad>'''	)
											self.assertEqual(len(SCREAMING_SNAKE_CASE_	) ,							1_008	)




							def 						__snake_case					(   self     :   Union[str, Any]	):
											self.assertEqual(self.get_tokenizer().vocab_size ,							1_008	)




							def 						__snake_case					(   self     :   int	):
											lowerCAmelCase__      			=						XGLMTokenizer(SCREAMING_SNAKE_CASE_ ,							keep_accents=SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						tokenizer.tokenize('''This is a test'''	)
											self.assertListEqual(SCREAMING_SNAKE_CASE_ ,							['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']	)

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_	) ,							[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]] ,							)

											lowerCAmelCase__      			=						tokenizer.tokenize('''I was born in 92000, and this is falsé.'''	)
											self.assertListEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        SPIECE_UNDERLINE + '''I''',
											        SPIECE_UNDERLINE + '''was''',
											        SPIECE_UNDERLINE + '''b''',
											        '''or''',
											        '''n''',
											        SPIECE_UNDERLINE + '''in''',
											        SPIECE_UNDERLINE + '''''',
											        '''9''',
											        '''2''',
											        '''0''',
											        '''0''',
											        '''0''',
											        ''',''',
											        SPIECE_UNDERLINE + '''and''',
											        SPIECE_UNDERLINE + '''this''',
											        SPIECE_UNDERLINE + '''is''',
											        SPIECE_UNDERLINE + '''f''',
											        '''al''',
											        '''s''',
											        '''é''',
											        '''.''',
											    ] ,							)
											lowerCAmelCase__      			=						tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_	)
											self.assertListEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        value + tokenizer.fairseq_offset
											        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
											    ] ,							)

											lowerCAmelCase__      			=						tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_	)
											self.assertListEqual(
											    SCREAMING_SNAKE_CASE_ ,							[
											        SPIECE_UNDERLINE + '''I''',
											        SPIECE_UNDERLINE + '''was''',
											        SPIECE_UNDERLINE + '''b''',
											        '''or''',
											        '''n''',
											        SPIECE_UNDERLINE + '''in''',
											        SPIECE_UNDERLINE + '''''',
											        '''<unk>''',
											        '''2''',
											        '''0''',
											        '''0''',
											        '''0''',
											        ''',''',
											        SPIECE_UNDERLINE + '''and''',
											        SPIECE_UNDERLINE + '''this''',
											        SPIECE_UNDERLINE + '''is''',
											        SPIECE_UNDERLINE + '''f''',
											        '''al''',
											        '''s''',
											        '''<unk>''',
											        '''.''',
											    ] ,							)




							@cached_property
							def 						__snake_case					(   self     :   List[str]	):
											return XGLMTokenizer.from_pretrained('''facebook/xglm-564M'''	)




							def 						__snake_case					(   self     :   Any	):
											with tempfile.NamedTemporaryFile() as f:
															shutil.copyfile(SCREAMING_SNAKE_CASE_ ,							f.name	)
															lowerCAmelCase__      			=						XGLMTokenizer(f.name ,							keep_accents=SCREAMING_SNAKE_CASE_	)
															lowerCAmelCase__      			=						pickle.dumps(SCREAMING_SNAKE_CASE_	)
											pickle.loads(SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Dict	):
											if not self.test_rust_tokenizer:
															return

											lowerCAmelCase__      			=						self.get_tokenizer()
											lowerCAmelCase__      			=						self.get_rust_tokenizer()

											lowerCAmelCase__      			=						'''I was born in 92000, and this is falsé.'''

											lowerCAmelCase__      			=						tokenizer.tokenize(SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_	)
											self.assertListEqual(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						tokenizer.encode(SCREAMING_SNAKE_CASE_ ,							add_special_tokens=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						rust_tokenizer.encode(SCREAMING_SNAKE_CASE_ ,							add_special_tokens=SCREAMING_SNAKE_CASE_	)
											self.assertListEqual(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						self.get_rust_tokenizer()
											lowerCAmelCase__      			=						tokenizer.encode(SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						rust_tokenizer.encode(SCREAMING_SNAKE_CASE_	)
											self.assertListEqual(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)




							@slow
							def 						__snake_case					(   self     :   Optional[Any]	):
											lowerCAmelCase__      			=						'''Hello World!'''
											lowerCAmelCase__      			=						[2, 31_227, 4_447, 35]

											self.assertListEqual(SCREAMING_SNAKE_CASE_ ,							self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_	)	)




							@slow
							def 						__snake_case					(   self     :   List[Any]	):
											lowerCAmelCase__      			=						(
											    '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
											    ''' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'''
											)
											# fmt: off
											lowerCAmelCase__      			=						[2, 1_018, 67, 11, 1_988, 2_617, 5_631, 278, 11, 3_407, 48, 71_630, 28_085, 4, 3_234, 157, 13, 6, 5, 6, 4, 3_526, 768, 15, 659, 57, 298, 3_983, 864, 129, 21, 6, 5, 13_675, 377, 652, 7_580, 10_341, 155, 2_817, 422, 1_666, 7, 1_674, 53, 113, 202_277, 17_892, 33, 60, 87, 4, 3_234, 157, 61, 2_667, 52_376, 19, 88, 23, 735]
											# fmt: on

											self.assertListEqual(SCREAMING_SNAKE_CASE_ ,							self.big_tokenizer.encode(SCREAMING_SNAKE_CASE_	)	)




							@slow
							def 						__snake_case					(   self     :   Dict	):
											# fmt: off
											lowerCAmelCase__      			=						{
											    '''input_ids''': [[2, 108_825, 1_163, 15, 88_010, 473, 15_898, 157, 13_672, 1_857, 312, 8, 238_021, 1_163, 53, 13_672, 1_857, 312, 8, 53_283, 182_396, 8, 18_566, 16, 36_733, 4_101, 8, 230, 244_017, 122_553, 7, 15, 132_597, 4, 293, 12_511, 7_610, 4, 3_414, 132_597, 9, 4, 32_361, 362, 4, 734, 28_512, 32_569, 18, 4, 32_361, 26_096, 14_982, 73, 18_715, 21_433, 235_261, 15, 492, 12_427, 16, 53, 18_715, 21_433, 65_454, 15, 23_659, 563, 16, 278, 597, 2_843, 595, 7_931, 182_396, 64_186, 22, 886, 595, 132_981, 53, 25_540, 3_449, 43_982, 39_901, 5_951, 878, 330, 4, 27_694, 80_269, 312, 53, 6_517, 11_780, 611, 20_408, 5], [2, 6, 132_597, 67, 42_897, 33, 592, 8, 163_729, 25_540, 361, 136_997, 109_514, 173_230, 7, 501, 60, 102_913, 196, 5_631, 235, 63_243, 473, 6, 231_757, 74, 5_277, 7_905, 53, 3_095, 37_317, 22, 454, 183_874, 5], [2, 268, 31_298, 46_530, 6, 132_935, 43_831, 7, 597, 32, 24, 3_688, 9_865, 5]],
											    '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
											}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=SCREAMING_SNAKE_CASE_ ,							model_name='''facebook/xglm-564M''' ,							padding=SCREAMING_SNAKE_CASE_ ,							)













import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class  lowerCAmelCase_       (				snake_case__					):
							UpperCamelCase_		:Tuple		      =    ['image_processor', 'tokenizer']
							UpperCamelCase_		:Tuple		      =    'ViTImageProcessor'
							UpperCamelCase_		:Dict		      =    ('CLIPTokenizer', 'CLIPTokenizerFast')




							def __init__(   self     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   Dict=None ,							SCREAMING_SNAKE_CASE_     :   Tuple=None ,							**SCREAMING_SNAKE_CASE_     :   Union[str, Any]	):
											lowerCAmelCase__      			=						None
											if "feature_extractor" in kwargs:
															warnings.warn(
															    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
															    ''' instead.''' ,							SCREAMING_SNAKE_CASE_ ,							)
															lowerCAmelCase__      			=						kwargs.pop('''feature_extractor'''	)

											lowerCAmelCase__      			=						image_processor if image_processor is not None else feature_extractor
											if image_processor is None:
															raise ValueError('''You need to specify an `image_processor`.'''	)
											if tokenizer is None:
															raise ValueError('''You need to specify a `tokenizer`.'''	)

											super().__init__(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)




							def __call__(   self     :   Dict ,							SCREAMING_SNAKE_CASE_     :   Any=None ,							SCREAMING_SNAKE_CASE_     :   Tuple=None ,							SCREAMING_SNAKE_CASE_     :   Dict=None ,							SCREAMING_SNAKE_CASE_     :   Optional[int]=None ,							**SCREAMING_SNAKE_CASE_     :   Optional[int]	):
											if text is None and visual_prompt is None and images is None:
															raise ValueError('''You have to specify either text, visual prompt or images.'''	)

											if text is not None and visual_prompt is not None:
															raise ValueError('''You have to specify exactly one type of prompt. Either text or visual prompt.'''	)

											if text is not None:
															lowerCAmelCase__      			=						self.tokenizer(SCREAMING_SNAKE_CASE_ ,							return_tensors=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)

											if visual_prompt is not None:
															lowerCAmelCase__      			=						self.image_processor(SCREAMING_SNAKE_CASE_ ,							return_tensors=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)

											if images is not None:
															lowerCAmelCase__      			=						self.image_processor(SCREAMING_SNAKE_CASE_ ,							return_tensors=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)

											if visual_prompt is not None and images is not None:
															lowerCAmelCase__      			=						{
															    '''pixel_values''': image_features.pixel_values,
															    '''conditional_pixel_values''': prompt_features.pixel_values,
															}
															return encoding
											elif text is not None and images is not None:
															lowerCAmelCase__      			=						image_features.pixel_values
															return encoding
											elif text is not None:
															return encoding
											elif visual_prompt is not None:
															lowerCAmelCase__      			=						{
															    '''conditional_pixel_values''': prompt_features.pixel_values,
															}
															return encoding
											else:
															return BatchEncoding(data=dict(**SCREAMING_SNAKE_CASE_	) ,							tensor_type=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Union[str, Any] ,							*SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							**SCREAMING_SNAKE_CASE_     :   str	):
											return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Optional[int] ,							*SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							**SCREAMING_SNAKE_CASE_     :   Tuple	):
											return self.tokenizer.decode(*SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)




							@property
							def 						__snake_case					(   self     :   str	):
											warnings.warn(
											    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.''' ,							SCREAMING_SNAKE_CASE_ ,							)
											return self.image_processor_class




							@property
							def 						__snake_case					(   self     :   Tuple	):
											warnings.warn(
											    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.''' ,							SCREAMING_SNAKE_CASE_ ,							)
											return self.image_processor





