






"""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


lowerCAmelCase_	:    List[Any]            =      DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

lowerCAmelCase_	:    Dict            =      '''main'''
# Default branch name
lowerCAmelCase_	:    str            =      '''f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'''
# One particular commit (not the top of `main`)
lowerCAmelCase_	:    List[Any]            =      '''aaaaaaa'''
# This commit does not exist, so we should 404.

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






@contextlib.contextmanager
def       _lowerCAmelCase       (      ):







       '''simple docstring'''
       print("""Welcome!"""		)
       yield
       print("""Bye!"""		)






@contextlib.contextmanager
def       _lowerCAmelCase       (      ):







       '''simple docstring'''
       print("""Bonjour!"""		)
       yield
       print("""Au revoir!"""		)





class   UpperCamelCase_ (       unittest.TestCase  ):



  def 		UpperCamelCase_				(      self				)			->			int:



         """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 		UpperCamelCase_				(      self ,		snake_case__				)			->			Any:



         """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 		UpperCamelCase_				(      self ,		snake_case__				)			->			int:



         """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 		UpperCamelCase_				(      self ,		snake_case__				)			->			List[Any]:



         """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 		UpperCamelCase_				(      self				)			->			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_ (       a_  ):
           pass





         self.assertEqual(find_labels(snake_case__				) ,		["""labels"""]				)



  @require_tf
  def 		UpperCamelCase_				(      self				)			->			Any:



         """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_ (       a_  ):
           pass





         self.assertEqual(find_labels(snake_case__				) ,		["""labels"""]				)



  @require_flax
  def 		UpperCamelCase_				(      self				)			->			Optional[Any]:



         """simple docstring"""





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





         class   UpperCamelCase_ (       a_  ):
           pass





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








"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase_	:    Optional[int]            =      {
    '''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_	:    str            =      [
     '''GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''GraphormerForGraphClassification''',
     '''GraphormerModel''',
     '''GraphormerPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_graphormer import (
      GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      GraphormerForGraphClassification,
      GraphormerModel,
      GraphormerPreTrainedModel,
  )


else:
 import sys

 lowerCAmelCase_	:    Optional[Any]            =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
