



"""simple docstring"""







import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
							from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
							from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
							from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


A    =			DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

A    =			'main'
# Default branch name
A    =			'f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'
# One particular commit (not the top of `main`)
A    =			'aaaaaaa'
# This commit does not exist, so we should 404.

A    =			'd9e9f15bc825e4b2c9249e9578f884bbcb5e3684'
# Sha-1 of config.json on the top of `main`, for checking purposes
A    =			'4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'

@contextlib.contextmanager
def   lowerCAmelCase__			(     ) ->							str:
							print('Welcome!'			)
							yield
							print('Bye!'			)

@contextlib.contextmanager
def   lowerCAmelCase__			(     ) ->							List[str]:
							print('Bonjour!'			)
							yield
							print('Au revoir!'			)






class      UpperCAmelCase__		(      unittest.TestCase     ):



		def 					A_		( self  :    Tuple				)			->						str:






									'''simple docstring'''

									assert transformers.__spec__ is not None
									assert importlib.util.find_spec('transformers'				) is not None






class      UpperCAmelCase__		(      unittest.TestCase     ):



		@unittest.mock.patch('sys.stdout'      ,							new_callable=io.StringIO				)
		def 					A_		( self  :    str      ,							snake_case  :    str				)			->						Dict:






									'''simple docstring'''

									with ContextManagers([]				):
																print('Transformers are awesome!'				)
									# The print statement adds a new line at the end of the output
									self.assertEqual(mock_stdout.getvalue()      ,							'Transformers are awesome!\n'				)



		@unittest.mock.patch('sys.stdout'      ,							new_callable=io.StringIO				)
		def 					A_		( self  :    List[str]      ,							snake_case  :    str				)			->						str:






									'''simple docstring'''

									with ContextManagers([context_en()]				):
																print('Transformers are awesome!'				)
									# The output should be wrapped with an English welcome and goodbye
									self.assertEqual(mock_stdout.getvalue()      ,							'Welcome!\nTransformers are awesome!\nBye!\n'				)



		@unittest.mock.patch('sys.stdout'      ,							new_callable=io.StringIO				)
		def 					A_		( self  :    List[str]      ,							snake_case  :    Tuple				)			->						str:






									'''simple docstring'''

									with ContextManagers([context_fr(), context_en()]				):
																print('Transformers are awesome!'				)
									# The output should be wrapped with an English and French welcome and goodbye
									self.assertEqual(mock_stdout.getvalue()      ,							'Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n'				)



		@require_torch
		def 					A_		( self  :    Optional[int]				)			->						int:






									'''simple docstring'''

									self.assertEqual(find_labels(snake_case				)      ,							['labels']				)
									self.assertEqual(find_labels(snake_case				)      ,							['labels', 'next_sentence_label']				)
									self.assertEqual(find_labels(snake_case				)      ,							['start_positions', 'end_positions']				)






									class      UpperCAmelCase__		(      UpperCamelCase     ):
											pass



									self.assertEqual(find_labels(snake_case				)      ,							['labels']				)



		@require_tf
		def 					A_		( self  :    Optional[Any]				)			->						str:






									'''simple docstring'''

									self.assertEqual(find_labels(snake_case				)      ,							['labels']				)
									self.assertEqual(find_labels(snake_case				)      ,							['labels', 'next_sentence_label']				)
									self.assertEqual(find_labels(snake_case				)      ,							['start_positions', 'end_positions']				)






									class      UpperCAmelCase__		(      UpperCamelCase     ):
											pass



									self.assertEqual(find_labels(snake_case				)      ,							['labels']				)



		@require_flax
		def 					A_		( self  :    int				)			->						List[str]:






									'''simple docstring'''

									self.assertEqual(find_labels(snake_case				)      ,							[]				)
									self.assertEqual(find_labels(snake_case				)      ,							[]				)
									self.assertEqual(find_labels(snake_case				)      ,							[]				)






									class      UpperCAmelCase__		(      UpperCamelCase     ):
											pass



									self.assertEqual(find_labels(snake_case				)      ,							[]				)








"""simple docstring"""







# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A    =			{'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A    =			[
							    'MRA_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'MraForMaskedLM',
							    'MraForMultipleChoice',
							    'MraForQuestionAnswering',
							    'MraForSequenceClassification',
							    'MraForTokenClassification',
							    'MraLayer',
							    'MraModel',
							    'MraPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mra import (
														    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MraForMaskedLM,
														    MraForMultipleChoice,
														    MraForQuestionAnswering,
														    MraForSequenceClassification,
														    MraForTokenClassification,
														    MraLayer,
														    MraModel,
														    MraPreTrainedModel,
														)
else:
							import sys

							A    =			_LazyModule(__name__, globals()['__file__'], _import_structure)



