'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase       :     int			=    logging.get_logger(__name__)

UpperCamelCase       :     Optional[Any]			=    {
    """google/electra-small-generator""": """https://huggingface.co/google/electra-small-generator/resolve/main/config.json""",
    """google/electra-base-generator""": """https://huggingface.co/google/electra-base-generator/resolve/main/config.json""",
    """google/electra-large-generator""": """https://huggingface.co/google/electra-large-generator/resolve/main/config.json""",
    """google/electra-small-discriminator""": (
        """https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json"""
    ),
    """google/electra-base-discriminator""": (
        """https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json"""
    ),
    """google/electra-large-discriminator""": (
        """https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json"""
    ),
}



class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    A     :    Dict				=			"electra"





    def __init__(					self     :						Any							,							UpperCAmelCase_     :						Dict=3_0_5_2_2							,							UpperCAmelCase_     :						List[str]=1_2_8							,							UpperCAmelCase_     :						Tuple=2_5_6							,							UpperCAmelCase_     :						Union[str, Any]=1_2							,							UpperCAmelCase_     :						str=4							,							UpperCAmelCase_     :						Any=1_0_2_4							,							UpperCAmelCase_     :						List[str]="gelu"							,							UpperCAmelCase_     :						Union[str, Any]=0.1							,							UpperCAmelCase_     :						int=0.1							,							UpperCAmelCase_     :						List[Any]=5_1_2							,							UpperCAmelCase_     :						int=2							,							UpperCAmelCase_     :						Dict=0.02							,							UpperCAmelCase_     :						Any=1e-12							,							UpperCAmelCase_     :						Dict="first"							,							UpperCAmelCase_     :						List[str]=True							,							UpperCAmelCase_     :						Union[str, Any]="gelu"							,							UpperCAmelCase_     :						Optional[int]=0.1							,							UpperCAmelCase_     :						List[Any]=0							,							UpperCAmelCase_     :						Optional[int]="absolute"							,							UpperCAmelCase_     :						Union[str, Any]=True							,							UpperCAmelCase_     :						str=None							,							**UpperCAmelCase_     :						Union[str, Any]							,							):


         """simple docstring"""







         super().__init__(pad_token_id=UpperCAmelCase_							,							**UpperCAmelCase_)

         a					:							Dict							= vocab_size
         a					:							Tuple							= embedding_size
         a					:							Optional[int]							= hidden_size
         a					:							Tuple							= num_hidden_layers
         a					:							Optional[Any]							= num_attention_heads
         a					:							Optional[int]							= intermediate_size
         a					:							List[str]							= hidden_act
         a					:							Any							= hidden_dropout_prob
         a					:							Optional[Any]							= attention_probs_dropout_prob
         a					:							str							= max_position_embeddings
         a					:							List[Any]							= type_vocab_size
         a					:							Optional[int]							= initializer_range
         a					:							Optional[Any]							= layer_norm_eps

         a					:							List[str]							= summary_type
         a					:							Optional[int]							= summary_use_proj
         a					:							List[str]							= summary_activation
         a					:							Optional[int]							= summary_last_dropout
         a					:							Any							= position_embedding_type
         a					:							Optional[Any]							= use_cache
         a					:							Tuple							= classifier_dropout






class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    @property
    def    SCREAMING_SNAKE_CASE_     (					self     :						List[Any]):


         """simple docstring"""







         if self.task == "multiple-choice":
              a					:							Any							= {0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
              a					:							Tuple							= {0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
                 ('token_type_ids', dynamic_axis),
             ])


'''simple docstring'''





import glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
      UpperCamelCase       :     List[Any]			=    []

      UpperCamelCase       :     Tuple			=    os.path.join("""tests""", """models""", """**""", """test_modeling_*.py""")
      UpperCamelCase       :     List[str]			=    glob.glob(pattern)
      # TODO: deal with TF/Flax too
      UpperCamelCase       :     List[Any]			=    [
          x for x in test_files if not (x.startswith("""test_modeling_tf_""") or x.startswith("""test_modeling_flax_"""))
      ]

      for test_file in test_files:
            UpperCamelCase       :     List[str]			=    get_tester_classes(test_file)
            for tester_class in tester_classes:
                  # A few tester classes don't have `parent` parameter in `__init__`.
                  # TODO: deal this better
                  try:
                        UpperCamelCase       :     int			=    tester_class(parent=None)
                  except Exception:
                        continue
                  if hasattr(tester, """get_config"""):
                        UpperCamelCase       :     Union[str, Any]			=    tester.get_config()
                        for k, v in config.to_dict().items():
                              if isinstance(v, int):
                                    UpperCamelCase       :     List[Any]			=    None
                                    if k in ["vocab_size"]:
                                          UpperCamelCase       :     List[Any]			=    100
                                    elif k in ["max_position_embeddings"]:
                                          UpperCamelCase       :     Tuple			=    128
                                    elif k in ["hidden_size", "d_model"]:
                                          UpperCamelCase       :     Any			=    40
                                    elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
                                          UpperCamelCase       :     Tuple			=    5
                                    if target is not None and v > target:
                                          failures.append(
                                              f'''{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'''
                                              f''' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'''
                                              f''' than {target}.'''
                                          )

      if len(failures) > 0:
            raise Exception(f'''There were {len(failures)} failures:\n''' + """\n""".join(failures))

