




'''simple docstring'''





import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')





def       __a      (  _UpperCamelCase:       List[Any]       )		->					List[Any]:

     """simple docstring"""




     _snake_case				= test_file.split(os.path.sep       )
     if components[0:2] != ["tests", "models"]:
          raise ValueError(
              "`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got "
              F"""{test_file} instead."""       )
     _snake_case				= components[-1]
     if not test_fn.endswith("py"       ):
          raise ValueError(F"""`test_file` should be a python file. Got {test_fn} instead."""       )
     if not test_fn.startswith("test_modeling_"       ):
          raise ValueError(
              F"""`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead."""       )

     _snake_case				= components[:-1] + [test_fn.replace(".py"   ,		""       )]
     _snake_case				= ".".join(_UpperCamelCase       )

     return test_module_path





def       __a      (  _UpperCamelCase:       List[Any]       )		->					int:

     """simple docstring"""




     _snake_case				= get_module_path(_UpperCamelCase       )
     _snake_case				= importlib.import_module(_UpperCamelCase       )

     return test_module





def       __a      (  _UpperCamelCase:       Optional[int]       )		->					str:

     """simple docstring"""




     _snake_case				= []
     _snake_case				= get_test_module(_UpperCamelCase       )
     for attr in dir(_UpperCamelCase       ):
          if attr.endswith("ModelTester"       ):
               tester_classes.append(getattr(_UpperCamelCase   ,		_UpperCamelCase       )       )

    # sort with class names
     return sorted(_UpperCamelCase   ,		key=lambda _UpperCamelCase       : x.__name__       )





def       __a      (  _UpperCamelCase:       Optional[Any]       )		->					Optional[int]:

     """simple docstring"""




     _snake_case				= []
     _snake_case				= get_test_module(_UpperCamelCase       )
     for attr in dir(_UpperCamelCase       ):
          _snake_case				= getattr(_UpperCamelCase   ,		_UpperCamelCase       )
          # (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
          # `all_model_classes` is not empty (which also excludes other special classes).
          _snake_case				= getattr(_UpperCamelCase   ,		"all_model_classes"   ,		[]       )
          if len(_UpperCamelCase       ) > 0:
               test_classes.append(_UpperCamelCase       )

    # sort with class names
     return sorted(_UpperCamelCase   ,		key=lambda _UpperCamelCase       : x.__name__       )





def       __a      (  _UpperCamelCase:       Dict       )		->					int:

     """simple docstring"""




     _snake_case				= get_test_classes(_UpperCamelCase       )
     _snake_case				= set()
     for test_class in test_classes:
          model_classes.update(test_class.all_model_classes       )

     # sort with class names
     return sorted(_UpperCamelCase   ,		key=lambda _UpperCamelCase       : x.__name__       )





def       __a      (  _UpperCamelCase:       Dict       )		->					Optional[int]:

     """simple docstring"""




     _snake_case				= test_class()
     if hasattr(_UpperCamelCase   ,		"setUp"       ):
          test.setUp()

     _snake_case				= None
     if hasattr(_UpperCamelCase   ,		"model_tester"       ):
          # `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
          if test.model_tester is not None:
               _snake_case				= test.model_tester.__class__

     return model_tester





def       __a      (  _UpperCamelCase:       str   ,		_UpperCamelCase:       Optional[Any]       )		->					Dict:

     """simple docstring"""




     _snake_case				= get_test_classes(_UpperCamelCase       )

     _snake_case				= []
     for test_class in test_classes:
          if model_class in test_class.all_model_classes:
               target_test_classes.append(_UpperCamelCase       )

    # sort with class names
     return sorted(_UpperCamelCase   ,		key=lambda _UpperCamelCase       : x.__name__       )





def       __a      (  _UpperCamelCase:       str   ,		_UpperCamelCase:       Optional[int]       )		->					Optional[int]:

     """simple docstring"""




     _snake_case				= get_test_classes_for_model(_UpperCamelCase   ,		_UpperCamelCase       )

     _snake_case				= []
     for test_class in test_classes:
          _snake_case				= get_model_tester_from_test_class(_UpperCamelCase       )
          if tester_class is not None:
               tester_classes.append(_UpperCamelCase       )

    # sort with class names
     return sorted(_UpperCamelCase   ,		key=lambda _UpperCamelCase       : x.__name__       )





def       __a      (  _UpperCamelCase:       Union[str, Any]       )		->					int:

     """simple docstring"""




     _snake_case				= get_test_classes(_UpperCamelCase       )
     _snake_case				= {test_class: get_model_tester_from_test_class(_UpperCamelCase       ) for test_class in test_classes}
     return test_tester_mapping





def       __a      (  _UpperCamelCase:       str       )		->					int:

     """simple docstring"""




     _snake_case				= get_model_classes(_UpperCamelCase       )
     _snake_case				= {
         model_class: get_test_classes_for_model(_UpperCamelCase   ,		_UpperCamelCase       ) for model_class in model_classes
     }
     return model_test_mapping





def       __a      (  _UpperCamelCase:       Any       )		->					List[str]:

     """simple docstring"""




     _snake_case				= get_model_classes(_UpperCamelCase       )
     _snake_case				= {
         model_class: get_tester_classes_for_model(_UpperCamelCase   ,		_UpperCamelCase       ) for model_class in model_classes
     }
     return model_to_tester_mapping





def       __a      (  _UpperCamelCase:       Optional[Any]       )		->					Tuple:

     """simple docstring"""




     if isinstance(_UpperCamelCase   ,		_UpperCamelCase       ):
          return o
     elif isinstance(_UpperCamelCase   ,		_UpperCamelCase       ):
          return o.__name__
     elif isinstance(_UpperCamelCase   ,		(list, tuple)       ):
          return [to_json(_UpperCamelCase       ) for x in o]
     elif isinstance(_UpperCamelCase   ,		_UpperCamelCase       ):
          return {to_json(_UpperCamelCase       ): to_json(_UpperCamelCase       ) for k, v in o.items()}
     else:
          return o








'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCamelCase_		:     Optional[Any]          =		{
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   pass

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCamelCase_		:     Union[str, Any]          =		[
       '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''RoCBertForCausalLM''',
       '''RoCBertForMaskedLM''',
       '''RoCBertForMultipleChoice''',
       '''RoCBertForPreTraining''',
       '''RoCBertForQuestionAnswering''',
       '''RoCBertForSequenceClassification''',
       '''RoCBertForTokenClassification''',
       '''RoCBertLayer''',
       '''RoCBertModel''',
       '''RoCBertPreTrainedModel''',
       '''load_tf_weights_in_roc_bert''',
   ]

if TYPE_CHECKING:
   from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
   from .tokenization_roc_bert import RoCBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      raise OptionalDependencyNotAvailable()

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_roc_bert import (
          ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          RoCBertForCausalLM,
          RoCBertForMaskedLM,
          RoCBertForMultipleChoice,
          RoCBertForPreTraining,
          RoCBertForQuestionAnswering,
          RoCBertForSequenceClassification,
          RoCBertForTokenClassification,
          RoCBertLayer,
          RoCBertModel,
          RoCBertPreTrainedModel,
          load_tf_weights_in_roc_bert,
      )


else:
   import sys

   UpperCamelCase_		:     int          =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


