





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  )		->				Any:
 UpperCamelCase			:      Any 			=     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."""  )
 UpperCamelCase			:      int 			=     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."""  )

 UpperCamelCase			:      List[str] 			=     components[:-1] + [test_fn.replace(".py"							,     ""  )]
 UpperCamelCase			:      Optional[int] 			=     ".".join(_lowerCAmelCase  )

 return test_module_path



def 	A_       (  _lowerCAmelCase  )		->				Any:
 UpperCamelCase			:      Optional[Any] 			=     get_module_path(_lowerCAmelCase  )
 UpperCamelCase			:      Any 			=     importlib.import_module(_lowerCAmelCase  )

 return test_module



def 	A_       (  _lowerCAmelCase  )		->				Union[str, Any]:
 UpperCamelCase			:      int 			=     []
 UpperCamelCase			:      Optional[Any] 			=     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  )		->				Optional[int]:
 UpperCamelCase			:      Dict 			=     []
 UpperCamelCase			:      Union[str, Any] 			=     get_test_module(_lowerCAmelCase  )
 for attr in dir(_lowerCAmelCase  ):
  UpperCamelCase			:      Any 			=     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).
  UpperCamelCase			:      List[Any] 			=     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  )		->				Any:
 UpperCamelCase			:      Tuple 			=     get_test_classes(_lowerCAmelCase  )
 UpperCamelCase			:      Dict 			=     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  )		->				Optional[int]:
 UpperCamelCase			:      Dict 			=     test_class()
 if hasattr(_lowerCAmelCase							,     "setUp"  ):
  test.setUp()

 UpperCamelCase			:      List[str] 			=     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:
   UpperCamelCase			:      List[Any] 			=     test.model_tester.__class__

 return model_tester



def 	A_       (  _lowerCAmelCase							,     _lowerCAmelCase  )		->				Dict:
 UpperCamelCase			:      int 			=     get_test_classes(_lowerCAmelCase  )

 UpperCamelCase			:      Union[str, Any] 			=     []
 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  )		->				Tuple:
 UpperCamelCase			:      str 			=     get_test_classes_for_model(_lowerCAmelCase							,     _lowerCAmelCase  )

 UpperCamelCase			:      str 			=     []
 for test_class in test_classes:
  UpperCamelCase			:      List[str] 			=     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  )		->				Union[str, Any]:
 UpperCamelCase			:      str 			=     get_test_classes(_lowerCAmelCase  )
 UpperCamelCase			:      str 			=     {test_class: get_model_tester_from_test_class(_lowerCAmelCase  ) for test_class in test_classes}
 return test_tester_mapping



def 	A_       (  _lowerCAmelCase  )		->				Optional[Any]:
 UpperCamelCase			:      str 			=     get_model_classes(_lowerCAmelCase  )
 UpperCamelCase			:      Tuple 			=     {
     model_class: get_test_classes_for_model(_lowerCAmelCase							,     _lowerCAmelCase  ) for model_class in model_classes
 }
 return model_test_mapping



def 	A_       (  _lowerCAmelCase  )		->				List[str]:
 UpperCamelCase			:      int 			=     get_model_classes(_lowerCAmelCase  )
 UpperCamelCase			:      Tuple 			=     {
     model_class: get_tester_classes_for_model(_lowerCAmelCase							,     _lowerCAmelCase  ) for model_class in model_classes
 }
 return model_to_tester_mapping



def 	A_       (  _lowerCAmelCase  )		->				str:
 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







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCamelCase :  Tuple										=  logging.get_logger(__name__)

__lowerCamelCase :  str										=  {
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}



class       A__     ( __snake_case    ):
      _UpperCAmelCase			:Union[str, Any]							=     'camembert'





      def __init__(				self ,							A_=3_0522 ,							A_=768 ,							A_=12 ,							A_=12 ,							A_=3072 ,							A_="gelu" ,							A_=0.1 ,							A_=0.1 ,							A_=512 ,							A_=2 ,							A_=0.02 ,							A_=1e-12 ,							A_=1 ,							A_=0 ,							A_=2 ,							A_="absolute" ,							A_=True ,							A_=None ,							**A_ ,							):
       '''simple docstring'''




       super().__init__(pad_token_id=A_ ,							bos_token_id=A_ ,							eos_token_id=A_ ,							**A_     )

       UpperCamelCase			:      List[str] 			=     vocab_size
       UpperCamelCase			:      Union[str, Any] 			=     hidden_size
       UpperCamelCase			:      Any 			=     num_hidden_layers
       UpperCamelCase			:      Union[str, Any] 			=     num_attention_heads
       UpperCamelCase			:      Dict 			=     hidden_act
       UpperCamelCase			:      str 			=     intermediate_size
       UpperCamelCase			:      str 			=     hidden_dropout_prob
       UpperCamelCase			:      Dict 			=     attention_probs_dropout_prob
       UpperCamelCase			:      Union[str, Any] 			=     max_position_embeddings
       UpperCamelCase			:      Optional[Any] 			=     type_vocab_size
       UpperCamelCase			:      int 			=     initializer_range
       UpperCamelCase			:      List[str] 			=     layer_norm_eps
       UpperCamelCase			:      Dict 			=     position_embedding_type
       UpperCamelCase			:      int 			=     use_cache
       UpperCamelCase			:      List[str] 			=     classifier_dropout



class       A__     ( __snake_case    ):





      @property
      def  __UpperCamelCase(				self     ):
       '''simple docstring'''




       if self.task == "multiple-choice":
        UpperCamelCase			:      Optional[int] 			=     {0: "batch", 1: "choice", 2: "sequence"}
       else:
        UpperCamelCase			:      str 			=     {0: "batch", 1: "sequence"}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
           ]     )
