



"""simple docstring"""






import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_lowercase : Dict      						=						get_tests_dir("fixtures/test_sentencepiece.model")

@require_sentencepiece
@require_tokenizers
class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_		,   unittest.TestCase   ):


					'''simple docstring'''





					_a   			=							ReformerTokenizer
					_a   			=							ReformerTokenizerFast
					_a   			=							True
					_a   			=							False
					_a   			=							True



					def 		snake_case       (       self							:  str     )->					Optional[int]:
								super().setUp()

								lowerCamelCase__		:		int			=ReformerTokenizer(lowerCamelCase,  keep_accents=lowerCamelCase     )
								tokenizer.save_pretrained(self.tmpdirname     )



					def 		snake_case       (       self							:  Optional[Any]     )->					int:
								lowerCamelCase__		:		Optional[Any]			='''<s>'''
								lowerCamelCase__		:		Optional[int]			=1

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



					def 		snake_case       (       self							:  Tuple     )->					Union[str, Any]:
								lowerCamelCase__		:		Optional[int]			=list(self.get_tokenizer().get_vocab().keys()     )

								self.assertEqual(vocab_keys[0],  '''<unk>'''     )
								self.assertEqual(vocab_keys[1],  '''<s>'''     )
								self.assertEqual(vocab_keys[-1],  '''j'''     )
								self.assertEqual(len(lowerCamelCase     ),  1000     )



					def 		snake_case       (       self							:  List[Any]     )->					Optional[int]:
								self.assertEqual(self.get_tokenizer().vocab_size,  1000     )



					def 		snake_case       (       self							:  Any     )->					List[Any]:
								if not self.test_rust_tokenizer:
											return

								lowerCamelCase__		:		Optional[int]			=self.get_tokenizer()
								lowerCamelCase__		:		str			=self.get_rust_tokenizer()

								lowerCamelCase__		:		Dict			='''I was born in 92000, and this is falsé.'''

								lowerCamelCase__		:		Optional[int]			=tokenizer.tokenize(lowerCamelCase     )
								lowerCamelCase__		:		Optional[int]			=rust_tokenizer.tokenize(lowerCamelCase     )
								self.assertListEqual(lowerCamelCase,  lowerCamelCase     )

								lowerCamelCase__		:		str			=tokenizer.encode(lowerCamelCase,  add_special_tokens=lowerCamelCase     )
								lowerCamelCase__		:		Any			=rust_tokenizer.encode(lowerCamelCase,  add_special_tokens=lowerCamelCase     )
								self.assertListEqual(lowerCamelCase,  lowerCamelCase     )

								lowerCamelCase__		:		str			=self.get_rust_tokenizer()
								lowerCamelCase__		:		Optional[int]			=tokenizer.encode(lowerCamelCase     )
								lowerCamelCase__		:		Union[str, Any]			=rust_tokenizer.encode(lowerCamelCase     )
								self.assertListEqual(lowerCamelCase,  lowerCamelCase     )



					def 		snake_case       (       self							:  int,  lowerCamelCase							:  List[str]=15     )->					int:
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
														lowerCamelCase__		:		Optional[Any]			=self.rust_tokenizer_class.from_pretrained(lowerCamelCase,  **lowerCamelCase     )

														# Simple input
														lowerCamelCase__		:		Optional[Any]			='''This is a simple input'''
														lowerCamelCase__		:		Optional[Any]			=['''This is a simple input 1''', '''This is a simple input 2''']
														lowerCamelCase__		:		List[Any]			=('''This is a simple input''', '''This is a pair''')
														lowerCamelCase__		:		Optional[int]			=[
														    ('''This is a simple input 1''', '''This is a simple input 2'''),
														    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
														]

														# Simple input tests
														self.assertRaises(lowerCamelCase,  tokenizer_r.encode,  lowerCamelCase,  max_length=lowerCamelCase,  padding='''max_length'''     )

														# Simple input
														self.assertRaises(lowerCamelCase,  tokenizer_r.encode_plus,  lowerCamelCase,  max_length=lowerCamelCase,  padding='''max_length'''     )

														# Simple input
														self.assertRaises(
														    lowerCamelCase,  tokenizer_r.batch_encode_plus,  lowerCamelCase,  max_length=lowerCamelCase,  padding='''max_length''',  )

														# Pair input
														self.assertRaises(lowerCamelCase,  tokenizer_r.encode,  lowerCamelCase,  max_length=lowerCamelCase,  padding='''max_length'''     )

														# Pair input
														self.assertRaises(lowerCamelCase,  tokenizer_r.encode_plus,  lowerCamelCase,  max_length=lowerCamelCase,  padding='''max_length'''     )

														# Pair input
														self.assertRaises(
														    lowerCamelCase,  tokenizer_r.batch_encode_plus,  lowerCamelCase,  max_length=lowerCamelCase,  padding='''max_length''',  )



					def 		snake_case       (       self							:  int     )->					Union[str, Any]:
								pass



					def 		snake_case       (       self							:  str     )->					Optional[int]:
								lowerCamelCase__		:		List[Any]			=ReformerTokenizer(lowerCamelCase,  keep_accents=lowerCamelCase     )

								lowerCamelCase__		:		List[str]			=tokenizer.tokenize('''This is a test'''     )
								self.assertListEqual(lowerCamelCase,  ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']     )

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(lowerCamelCase     ),  [285, 46, 10, 170, 382],  )

								lowerCamelCase__		:		List[str]			=tokenizer.tokenize('''I was born in 92000, and this is falsé.'''     )
								self.assertListEqual(
								    lowerCamelCase,  [
								        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__		:		Tuple			=tokenizer.convert_tokens_to_ids(lowerCamelCase     )
								self.assertListEqual(
								    lowerCamelCase,  [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4],  )

								lowerCamelCase__		:		int			=tokenizer.convert_ids_to_tokens(lowerCamelCase     )
								self.assertListEqual(
								    lowerCamelCase,  [
								        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							:  Optional[Any]     )->					str:
								return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment'''     )



					@slow
					def 		snake_case       (       self							:  Dict     )->					Any:
								lowerCamelCase__		:		Dict			='''Hello World!'''
								lowerCamelCase__		:		Tuple			=[126, 32, 262, 152, 38, 72, 287]

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



					@slow
					def 		snake_case       (       self							:  Optional[Any]     )->					Any:
								lowerCamelCase__		:		str			=(
								    '''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'''
								)
								lowerCamelCase__		:		List[str]			=[
								    108,
								    265,
								    24,
								    111,
								    4,
								    258,
								    156,
								    35,
								    28,
								    275,
								    3,
								    259,
								    297,
								    260,
								    84,
								    4,
								    35,
								    110,
								    44,
								    8,
								    259,
								    91,
								    268,
								    21,
								    11,
								    209,
								    274,
								    109,
								    266,
								    277,
								    117,
								    86,
								    93,
								    315,
								    258,
								    278,
								    258,
								    277,
								    258,
								    0,
								    258,
								    288,
								    258,
								    319,
								    258,
								    0,
								    258,
								    0,
								    258,
								    0,
								    258,
								    0,
								    258,
								    287,
								    258,
								    315,
								    258,
								    289,
								    258,
								    278,
								    99,
								    269,
								    266,
								    262,
								    8,
								    259,
								    241,
								    4,
								    217,
								    230,
								    268,
								    266,
								    55,
								    168,
								    106,
								    75,
								    193,
								    266,
								    223,
								    27,
								    49,
								    26,
								    282,
								    25,
								    264,
								    299,
								    19,
								    26,
								    0,
								    258,
								    277,
								    117,
								    86,
								    93,
								    176,
								    183,
								    270,
								    11,
								    262,
								    42,
								    61,
								    265,
								]

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



					@require_torch
					@slow
					def 		snake_case       (       self							:  Any     )->					Tuple:
								import torch

								from transformers import ReformerConfig, ReformerModel

								# Build sequence
								lowerCamelCase__		:		Optional[int]			=list(self.big_tokenizer.get_vocab().keys()     )[:10]
								lowerCamelCase__		:		str			=''' '''.join(lowerCamelCase     )
								lowerCamelCase__		:		int			=self.big_tokenizer.encode_plus(lowerCamelCase,  return_tensors='''pt'''     )
								lowerCamelCase__		:		int			=self.big_tokenizer.batch_encode_plus([sequence, sequence],  return_tensors='''pt'''     )

								lowerCamelCase__		:		int			=ReformerConfig()
								# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
								lowerCamelCase__		:		Any			=encoded_sequence['''input_ids'''].shape
								lowerCamelCase__		:		Union[str, Any]			=ReformerModel(lowerCamelCase     )

								# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
								assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

								with torch.no_grad():
											model(**lowerCamelCase     )
											model(**lowerCamelCase     )




					@slow
					def 		snake_case       (       self							:  Optional[int]     )->					Tuple:
								# fmt: off
								lowerCamelCase__		:		Union[str, Any]			={'''input_ids''': [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], '''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]]}  # noqa: E501
								# fmt: on

								# This tokenizer does not know some characters like ")".
								# That is the reason why we use very simple texts here.
								# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
								lowerCamelCase__		:		Optional[int]			=[
								    '''This is a very simple sentence.''',
								    '''The quick brown fox jumps over the lazy dog.''',
								]

								self.tokenizer_integration_test_util(
								    expected_encoding=lowerCamelCase,  model_name='''google/reformer-crime-and-punishment''',  revision='''0e6c3decb8211d49bf881013425dc8b0448b3f5a''',  padding=lowerCamelCase,  sequences=lowerCamelCase,  )









"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor


_lowercase : Any      						=						logging.get_logger(__name__)

class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_   ):


					'''simple docstring'''





					def __init__(       self							:  Any,  *lowerCamelCase							:  str,  **lowerCamelCase							:  Optional[Any]     )->					None:
								warnings.warn(
								    '''The class OwlViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
								    ''' use OwlViTImageProcessor instead.''',  lowerCamelCase,  )
								super().__init__(*lowerCamelCase,  **lowerCamelCase     )




