


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   (lowerCAmelCase__   ):
   __a					=  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.'''   )
   __a					=  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.'''   )

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

   return test_module_path




def  a   (lowerCAmelCase__   ):
   __a					=  get_module_path(lowerCAmelCase__   )
   __a					=  importlib.import_module(lowerCAmelCase__   )

   return test_module




def  a   (lowerCAmelCase__   ):
   __a					=  []
   __a					=  get_test_module(lowerCAmelCase__   )
   for attr in dir(lowerCAmelCase__   ):
      if attr.endswith("""ModelTester"""   ):
         tester_classes.append(getattr(lowerCAmelCase__		,				lowerCAmelCase__   )   )

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




def  a   (lowerCAmelCase__   ):
   __a					=  []
   __a					=  get_test_module(lowerCAmelCase__   )
   for attr in dir(lowerCAmelCase__   ):
      __a					=  getattr(lowerCAmelCase__		,				lowerCAmelCase__   )
      # (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).
      __a					=  getattr(lowerCAmelCase__		,				"""all_model_classes"""		,				[]   )
      if len(lowerCAmelCase__   ) > 0:
         test_classes.append(lowerCAmelCase__   )

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




def  a   (lowerCAmelCase__   ):
   __a					=  get_test_classes(lowerCAmelCase__   )
   __a					=  set()
   for test_class in test_classes:
      model_classes.update(test_class.all_model_classes   )

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




def  a   (lowerCAmelCase__   ):
   __a					=  test_class()
   if hasattr(lowerCAmelCase__		,				"""setUp"""   ):
      test.setUp()

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

   return model_tester




def  a   (lowerCAmelCase__		,				lowerCAmelCase__   ):
   __a					=  get_test_classes(lowerCAmelCase__   )

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

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




def  a   (lowerCAmelCase__		,				lowerCAmelCase__   ):
   __a					=  get_test_classes_for_model(lowerCAmelCase__		,				lowerCAmelCase__   )

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

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




def  a   (lowerCAmelCase__   ):
   __a					=  get_test_classes(lowerCAmelCase__   )
   __a					=  {test_class: get_model_tester_from_test_class(lowerCAmelCase__   ) for test_class in test_classes}
   return test_tester_mapping




def  a   (lowerCAmelCase__   ):
   __a					=  get_model_classes(lowerCAmelCase__   )
   __a					=  {
       model_class: get_test_classes_for_model(lowerCAmelCase__		,				lowerCAmelCase__   ) for model_class in model_classes
   }
   return model_test_mapping




def  a   (lowerCAmelCase__   ):
   __a					=  get_model_classes(lowerCAmelCase__   )
   __a					=  {
       model_class: get_tester_classes_for_model(lowerCAmelCase__		,				lowerCAmelCase__   ) for model_class in model_classes
   }
   return model_to_tester_mapping




def  a   (lowerCAmelCase__   ):
   if isinstance(lowerCAmelCase__		,				lowerCAmelCase__   ):
      return o
   elif isinstance(lowerCAmelCase__		,				lowerCAmelCase__   ):
      return o.__name__
   elif isinstance(lowerCAmelCase__		,				(list, tuple)   ):
      return [to_json(lowerCAmelCase__   ) for x in o]
   elif isinstance(lowerCAmelCase__		,				lowerCAmelCase__   ):
      return {to_json(lowerCAmelCase__   ): to_json(lowerCAmelCase__   ) 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__)


