





"""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 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[Any]			):
 lowerCAmelCase    				= 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.'			)
 lowerCAmelCase    				= 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.'			)

 lowerCAmelCase    				= components[:-1] + [test_fn.replace('.py'  ,     ''			)]
 lowerCAmelCase    				= '.'.join(_UpperCAmelCase			)

 return test_module_path

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Tuple			):
 lowerCAmelCase    				= get_module_path(_UpperCAmelCase			)
 lowerCAmelCase    				= importlib.import_module(_UpperCAmelCase			)

 return test_module

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Dict			):
 lowerCAmelCase    				= []
 lowerCAmelCase    				= 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 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Union[str, Any]			):
 lowerCAmelCase    				= []
 lowerCAmelCase    				= get_test_module(_UpperCAmelCase			)
 for attr in dir(_UpperCAmelCase			):
  lowerCAmelCase    				= 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).
  lowerCAmelCase    				= 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 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Dict			):
 lowerCAmelCase    				= get_test_classes(_UpperCAmelCase			)
 lowerCAmelCase    				= 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 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[str]			):
 lowerCAmelCase    				= test_class()
 if hasattr(_UpperCAmelCase  ,     'setUp'			):
  test.setUp()

 lowerCAmelCase    				= 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:
   lowerCAmelCase    				= test.model_tester.__class__

 return model_tester

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    int  ,     _UpperCAmelCase					:    Union[str, Any]			):
 lowerCAmelCase    				= get_test_classes(_UpperCAmelCase			)

 lowerCAmelCase    				= []
 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 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[str]  ,     _UpperCAmelCase					:    int			):
 lowerCAmelCase    				= get_test_classes_for_model(_UpperCAmelCase  ,     _UpperCAmelCase			)

 lowerCAmelCase    				= []
 for test_class in test_classes:
  lowerCAmelCase    				= 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 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    int			):
 lowerCAmelCase    				= get_test_classes(_UpperCAmelCase			)
 lowerCAmelCase    				= {test_class: get_model_tester_from_test_class(_UpperCAmelCase			) for test_class in test_classes}
 return test_tester_mapping

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Any			):
 lowerCAmelCase    				= get_model_classes(_UpperCAmelCase			)
 lowerCAmelCase    				= {
     model_class: get_test_classes_for_model(_UpperCAmelCase  ,     _UpperCAmelCase			) for model_class in model_classes
 }
 return model_test_mapping

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Tuple			):
 lowerCAmelCase    				= get_model_classes(_UpperCAmelCase			)
 lowerCAmelCase    				= {
     model_class: get_tester_classes_for_model(_UpperCAmelCase  ,     _UpperCAmelCase			) for model_class in model_classes
 }
 return model_to_tester_mapping




def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Optional[Any]			):
 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











from typing import TYPE_CHECKING

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


__magic_name__  :  Optional[int]					=       {
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  int					=       [
          """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """BioGptForCausalLM""",
          """BioGptForTokenClassification""",
          """BioGptForSequenceClassification""",
          """BioGptModel""",
          """BioGptPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
      from .tokenization_biogpt import BioGptTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_biogpt import (
                BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BioGptForCausalLM,
                BioGptForSequenceClassification,
                BioGptForTokenClassification,
                BioGptModel,
                BioGptPreTrainedModel,
            )


else:
      import sys

      __magic_name__  :  int					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

