





'''simple docstring'''

import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
			from test_module.custom_tokenization_fast import CustomTokenizerFast
class     __lowerCAmelCase					(   unittest.TestCase			):






							"""simple docstring"""





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

												'''simple docstring'''




												_UpperCamelCase       =	0





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

												'''simple docstring'''




												for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
																	self.assertIsNotNone(lowerCAmelCase__					)
																	self.assertIsInstance(lowerCAmelCase__	,			(BertTokenizer, BertTokenizerFast)					)
																	self.assertGreater(len(lowerCAmelCase__					)	,			0					)

												for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
																	self.assertIsNotNone(lowerCAmelCase__					)
																	self.assertIsInstance(lowerCAmelCase__	,			(GPTaTokenizer, GPTaTokenizerFast)					)
																	self.assertGreater(len(lowerCAmelCase__					)	,			0					)





							def snake_case__						(							self       :		Dict					)   ->					Dict:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
												self.assertIsInstance(lowerCAmelCase__	,			(BertTokenizer, BertTokenizerFast)					)
												self.assertEqual(tokenizer.vocab_size	,			12					)





							def snake_case__						(							self       :		List[str]					)   ->					Union[str, Any]:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
												self.assertIsInstance(lowerCAmelCase__	,			(RobertaTokenizer, RobertaTokenizerFast)					)
												self.assertEqual(tokenizer.vocab_size	,			20					)





							def snake_case__						(							self       :		List[str]					)   ->					Union[str, Any]:

												'''simple docstring'''




												_UpperCamelCase       =	AutoConfig.from_pretrained(lowerCAmelCase__					)
												self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)
												# Check that tokenizer_type ≠ model_type
												_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			config=lowerCAmelCase__					)
												self.assertIsInstance(lowerCAmelCase__	,			(BertTokenizer, BertTokenizerFast)					)
												self.assertEqual(tokenizer.vocab_size	,			12					)





							def snake_case__						(							self       :		List[Any]					)   ->					List[str]:

												'''simple docstring'''




												with tempfile.TemporaryDirectory() as tmp_dir:
																	shutil.copy('''./tests/fixtures/vocab.txt'''	,			os.path.join(lowerCAmelCase__	,			'''vocab.txt'''					)					)

																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			tokenizer_type='''bert'''	,			use_fast=lowerCAmelCase__					)
																	self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)

												with tempfile.TemporaryDirectory() as tmp_dir:
																	shutil.copy('''./tests/fixtures/vocab.json'''	,			os.path.join(lowerCAmelCase__	,			'''vocab.json'''					)					)
																	shutil.copy('''./tests/fixtures/merges.txt'''	,			os.path.join(lowerCAmelCase__	,			'''merges.txt'''					)					)

																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			tokenizer_type='''gpt2'''	,			use_fast=lowerCAmelCase__					)
																	self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)





							@require_tokenizers
							def snake_case__						(							self       :		Optional[Any]					)   ->					str:

												'''simple docstring'''




												with tempfile.TemporaryDirectory() as tmp_dir:
																	shutil.copy('''./tests/fixtures/vocab.txt'''	,			os.path.join(lowerCAmelCase__	,			'''vocab.txt'''					)					)

																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			tokenizer_type='''bert'''					)
																	self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)

												with tempfile.TemporaryDirectory() as tmp_dir:
																	shutil.copy('''./tests/fixtures/vocab.json'''	,			os.path.join(lowerCAmelCase__	,			'''vocab.json'''					)					)
																	shutil.copy('''./tests/fixtures/merges.txt'''	,			os.path.join(lowerCAmelCase__	,			'''merges.txt'''					)					)

																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			tokenizer_type='''gpt2'''					)
																	self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)





							def snake_case__						(							self       :		Tuple					)   ->					Optional[Any]:

												'''simple docstring'''




												with pytest.raises(lowerCAmelCase__					):
																	AutoTokenizer.from_pretrained('''./'''	,			tokenizer_type='''xxx'''					)





							@require_tokenizers
							def snake_case__						(							self       :		str					)   ->					Any:

												'''simple docstring'''




												for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
																	_UpperCamelCase       =	tokenizer_class.from_pretrained('''wietsedv/bert-base-dutch-cased'''					)
																	self.assertIsInstance(lowerCAmelCase__	,			(BertTokenizer, BertTokenizerFast)					)

																	if isinstance(lowerCAmelCase__	,			lowerCAmelCase__					):
																						self.assertEqual(tokenizer.basic_tokenizer.do_lower_case	,			lowerCAmelCase__					)
																	else:
																						self.assertEqual(tokenizer.do_lower_case	,			lowerCAmelCase__					)

																	self.assertEqual(tokenizer.model_max_length	,			512					)





							@require_tokenizers
							def snake_case__						(							self       :		Optional[int]					)   ->					Dict:

												'''simple docstring'''




												for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
																	with self.assertRaisesRegex(
																	    lowerCAmelCase__	,			'''julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier'''	,			):
																						_UpperCamelCase       =	tokenizer_class.from_pretrained('''julien-c/herlolip-not-exists'''					)





							def snake_case__						(							self       :		Optional[int]					)   ->					Union[str, Any]:

												'''simple docstring'''




												_UpperCamelCase       =	TOKENIZER_MAPPING.values()
												_UpperCamelCase       =	[]

												for slow_tok, fast_tok in tokenizers:
																	if slow_tok is not None:
																						tokenizer_names.append(slow_tok.__name__					)

																	if fast_tok is not None:
																						tokenizer_names.append(fast_tok.__name__					)

												for tokenizer_name in tokenizer_names:
																	# must find the right class
																	tokenizer_class_from_name(lowerCAmelCase__					)





							@require_tokenizers
							def snake_case__						(							self       :		int					)   ->					List[Any]:

												'''simple docstring'''




												self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''	,			use_fast=lowerCAmelCase__					)	,			lowerCAmelCase__					)
												self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''					)	,			lowerCAmelCase__					)





							@require_tokenizers
							def snake_case__						(							self       :		Optional[int]					)   ->					str:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained('''distilbert-base-uncased'''	,			do_lower_case=lowerCAmelCase__					)
												_UpperCamelCase       =	'''Hello, world. How are you?'''
												_UpperCamelCase       =	tokenizer.tokenize(lowerCAmelCase__					)
												self.assertEqual('''[UNK]'''	,			tokens[0]					)

												_UpperCamelCase       =	AutoTokenizer.from_pretrained('''microsoft/mpnet-base'''	,			do_lower_case=lowerCAmelCase__					)
												_UpperCamelCase       =	tokenizer.tokenize(lowerCAmelCase__					)
												self.assertEqual('''[UNK]'''	,			tokens[0]					)





							@require_tokenizers
							def snake_case__						(							self       :		Optional[int]					)   ->					int:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained('''robot-test/dummy-tokenizer-fast-with-model-config'''					)
												self.assertEqual(type(lowerCAmelCase__					)	,			lowerCAmelCase__					)
												self.assertEqual(tokenizer.model_max_length	,			512					)
												self.assertEqual(tokenizer.vocab_size	,			30000					)
												self.assertEqual(tokenizer.unk_token	,			'''[UNK]'''					)
												self.assertEqual(tokenizer.padding_side	,			'''right'''					)
												self.assertEqual(tokenizer.truncation_side	,			'''right'''					)





							def snake_case__						(							self       :		str					)   ->					Optional[Any]:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
												self.assertIsInstance(lowerCAmelCase__	,			(BertTokenizer, BertTokenizerFast)					)
												with tempfile.TemporaryDirectory() as tmp_dir:
																	tokenizer.save_pretrained(lowerCAmelCase__					)
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)

												self.assertIsInstance(lowerCAmelCase__	,			tokenizer.__class__					)
												self.assertEqual(tokenizera.vocab_size	,			12					)





							def snake_case__						(							self       :		str					)   ->					Tuple:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained('''ctrl'''					)
												# There is no fast CTRL so this always gives us a slow tokenizer.
												self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)





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

												'''simple docstring'''




												_UpperCamelCase       =	get_tokenizer_config('''bert-base-cased'''					)
												_UpperCamelCase       =	config.pop('''_commit_hash'''	,			lowerCAmelCase__					)
												# If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
												self.assertEqual(lowerCAmelCase__	,			{'''do_lower_case''': False}					)

												# This model does not have a tokenizer_config so we get back an empty dict.
												_UpperCamelCase       =	get_tokenizer_config(lowerCAmelCase__					)
												self.assertDictEqual(lowerCAmelCase__	,			{}					)

												# A tokenizer saved with `save_pretrained` always creates a tokenizer config.
												_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
												with tempfile.TemporaryDirectory() as tmp_dir:
																	tokenizer.save_pretrained(lowerCAmelCase__					)
																	_UpperCamelCase       =	get_tokenizer_config(lowerCAmelCase__					)

												# Check the class of the tokenizer was properly saved (note that it always saves the slow class).
												self.assertEqual(config['''tokenizer_class''']	,			'''BertTokenizer'''					)





							def snake_case__						(							self       :		List[Any]					)   ->					Union[str, Any]:

												'''simple docstring'''




												try:
																	AutoConfig.register('''custom'''	,			lowerCAmelCase__					)

																	AutoTokenizer.register(lowerCAmelCase__	,			slow_tokenizer_class=lowerCAmelCase__					)
																	# Trying to register something existing in the Transformers library will raise an error
																	with self.assertRaises(lowerCAmelCase__					):
																						AutoTokenizer.register(lowerCAmelCase__	,			slow_tokenizer_class=lowerCAmelCase__					)

																	_UpperCamelCase       =	CustomTokenizer.from_pretrained(lowerCAmelCase__					)
																	with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer.save_pretrained(lowerCAmelCase__					)

																						_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
																						self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)

												finally:
																	if "custom" in CONFIG_MAPPING._extra_content:
																						del CONFIG_MAPPING._extra_content["custom"]
																	if CustomConfig in TOKENIZER_MAPPING._extra_content:
																						del TOKENIZER_MAPPING._extra_content[CustomConfig]





							@require_tokenizers
							def snake_case__						(							self       :		Tuple					)   ->					List[Any]:

												'''simple docstring'''




												try:
																	AutoConfig.register('''custom'''	,			lowerCAmelCase__					)

																	# Can register in two steps
																	AutoTokenizer.register(lowerCAmelCase__	,			slow_tokenizer_class=lowerCAmelCase__					)
																	self.assertEqual(TOKENIZER_MAPPING[CustomConfig]	,			(CustomTokenizer, None)					)
																	AutoTokenizer.register(lowerCAmelCase__	,			fast_tokenizer_class=lowerCAmelCase__					)
																	self.assertEqual(TOKENIZER_MAPPING[CustomConfig]	,			(CustomTokenizer, CustomTokenizerFast)					)

																	del TOKENIZER_MAPPING._extra_content[CustomConfig]
																	# Can register in one step
																	AutoTokenizer.register(
																	    lowerCAmelCase__	,			slow_tokenizer_class=lowerCAmelCase__	,			fast_tokenizer_class=lowerCAmelCase__					)
																	self.assertEqual(TOKENIZER_MAPPING[CustomConfig]	,			(CustomTokenizer, CustomTokenizerFast)					)

																	# Trying to register something existing in the Transformers library will raise an error
																	with self.assertRaises(lowerCAmelCase__					):
																						AutoTokenizer.register(lowerCAmelCase__	,			fast_tokenizer_class=lowerCAmelCase__					)

																	# We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
																	# and that model does not have a tokenizer.json
																	with tempfile.TemporaryDirectory() as tmp_dir:
																						_UpperCamelCase       =	BertTokenizerFast.from_pretrained(lowerCAmelCase__					)
																						bert_tokenizer.save_pretrained(lowerCAmelCase__					)
																						_UpperCamelCase       =	CustomTokenizerFast.from_pretrained(lowerCAmelCase__					)

																	with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer.save_pretrained(lowerCAmelCase__					)

																						_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__					)
																						self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)

																						_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			use_fast=lowerCAmelCase__					)
																						self.assertIsInstance(lowerCAmelCase__	,			lowerCAmelCase__					)

												finally:
																	if "custom" in CONFIG_MAPPING._extra_content:
																						del CONFIG_MAPPING._extra_content["custom"]
																	if CustomConfig in TOKENIZER_MAPPING._extra_content:
																						del TOKENIZER_MAPPING._extra_content[CustomConfig]





							def snake_case__						(							self       :		int					)   ->					Dict:

												'''simple docstring'''




												with self.assertRaises(lowerCAmelCase__					):
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''					)
												# If remote code is disabled, we can't load this config.
												with self.assertRaises(lowerCAmelCase__					):
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__					)

												_UpperCamelCase       =	AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__					)
												self.assertTrue(tokenizer.special_attribute_present					)
												# Test tokenizer can be reloaded.
												with tempfile.TemporaryDirectory() as tmp_dir:
																	tokenizer.save_pretrained(lowerCAmelCase__					)
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			trust_remote_code=lowerCAmelCase__					)
												self.assertTrue(reloaded_tokenizer.special_attribute_present					)

												if is_tokenizers_available():
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizerFast'''					)
																	self.assertEqual(reloaded_tokenizer.__class__.__name__	,			'''NewTokenizerFast'''					)

																	# Test we can also load the slow version
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__	,			use_fast=lowerCAmelCase__					)
																	self.assertTrue(tokenizer.special_attribute_present					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
																	# Test tokenizer can be reloaded.
																	with tempfile.TemporaryDirectory() as tmp_dir:
																						tokenizer.save_pretrained(lowerCAmelCase__					)
																						_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			trust_remote_code=lowerCAmelCase__	,			use_fast=lowerCAmelCase__					)
																	self.assertEqual(reloaded_tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
																	self.assertTrue(reloaded_tokenizer.special_attribute_present					)
												else:
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
																	self.assertEqual(reloaded_tokenizer.__class__.__name__	,			'''NewTokenizer'''					)





							@require_tokenizers
							def snake_case__						(							self       :		Union[str, Any]					)   ->					List[str]:

												'''simple docstring'''




												class     __lowerCAmelCase					(   __magic_name__			):






																			"""simple docstring"""
																			_snake_case     :					Dict						    =   False

												class     __lowerCAmelCase					(   __magic_name__			):






																			"""simple docstring"""
																			_snake_case     :					int						    =   NewTokenizer
																			_snake_case     :					Union[str, Any]						    =   False

												try:
																	AutoConfig.register('''custom'''	,			lowerCAmelCase__					)
																	AutoTokenizer.register(lowerCAmelCase__	,			slow_tokenizer_class=lowerCAmelCase__					)
																	AutoTokenizer.register(lowerCAmelCase__	,			fast_tokenizer_class=lowerCAmelCase__					)
																	# If remote code is not set, the default is to use local
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizerFast'''					)
																	self.assertFalse(tokenizer.special_attribute_present					)
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''	,			use_fast=lowerCAmelCase__					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
																	self.assertFalse(tokenizer.special_attribute_present					)

																	# If remote code is disabled, we load the local one.
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizerFast'''					)
																	self.assertFalse(tokenizer.special_attribute_present					)
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__	,			use_fast=lowerCAmelCase__					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
																	self.assertFalse(tokenizer.special_attribute_present					)

																	# If remote is enabled, we load from the Hub
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizerFast'''					)
																	self.assertTrue(tokenizer.special_attribute_present					)
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer'''	,			trust_remote_code=lowerCAmelCase__	,			use_fast=lowerCAmelCase__					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
																	self.assertTrue(tokenizer.special_attribute_present					)

												finally:
																	if "custom" in CONFIG_MAPPING._extra_content:
																						del CONFIG_MAPPING._extra_content["custom"]
																	if CustomConfig in TOKENIZER_MAPPING._extra_content:
																						del TOKENIZER_MAPPING._extra_content[CustomConfig]





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

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained(
												    '''hf-internal-testing/test_dynamic_tokenizer_legacy'''	,			trust_remote_code=lowerCAmelCase__					)
												self.assertTrue(tokenizer.special_attribute_present					)
												if is_tokenizers_available():
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizerFast'''					)

																	# Test we can also load the slow version
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(
																	    '''hf-internal-testing/test_dynamic_tokenizer_legacy'''	,			trust_remote_code=lowerCAmelCase__	,			use_fast=lowerCAmelCase__					)
																	self.assertTrue(tokenizer.special_attribute_present					)
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)
												else:
																	self.assertEqual(tokenizer.__class__.__name__	,			'''NewTokenizer'''					)





							def snake_case__						(							self       :		Any					)   ->					int:

												'''simple docstring'''




												with self.assertRaisesRegex(
												    lowerCAmelCase__	,			'''bert-base is not a local folder and is not a valid model identifier'''					):
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained('''bert-base'''					)





							def snake_case__						(							self       :		int					)   ->					List[Any]:

												'''simple docstring'''




												with self.assertRaisesRegex(
												    lowerCAmelCase__	,			r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''					):
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained(lowerCAmelCase__	,			revision='''aaaaaa'''					)







							def snake_case__						(							self       :		Dict					)   ->					List[str]:

												'''simple docstring'''




												_UpperCamelCase       =	AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''					)
												with RequestCounter() as counter:
																	_UpperCamelCase       =	AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''					)
																	self.assertEqual(counter.get_request_count	,			0					)
																	self.assertEqual(counter.head_request_count	,			1					)
																	self.assertEqual(counter.other_request_count	,			0					)










'''simple docstring'''

import warnings

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


lowercase__						:      Optional[Any]	=    logging.get_logger(__name__)
class     __lowerCAmelCase					(   __magic_name__			):






       """simple docstring"""





       def __init__(							self       :		List[Any]	,			*lowerCAmelCase__       :		List[str]	,			**lowerCAmelCase__       :		List[str]					)   ->					None:

            '''simple docstring'''




            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__					)



