




import glob
import os

from get_test_info import get_tester_classes


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

   UpperCAmelCase__    :							int       		=     os.path.join('tests', 'models', '**', 'test_modeling_*.py')
   UpperCAmelCase__    :							List[Any]       		=     glob.glob(pattern)
   # TODO: deal with TF/Flax too
   UpperCAmelCase__    :							str       		=     [
       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[Any]       		=     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__    :							Dict       		=     tester_class(parent=None)
         except Exception:
            continue
         if hasattr(tester, 'get_config'):
            UpperCAmelCase__    :							Optional[int]       		=     tester.get_config()
            for k, v in config.to_dict().items():
               if isinstance(v, int):
                  UpperCAmelCase__    :							List[str]       		=     None
                  if k in ["vocab_size"]:
                     UpperCAmelCase__    :							List[str]       		=     100
                  elif k in ["max_position_embeddings"]:
                     UpperCAmelCase__    :							List[Any]       		=     128
                  elif k in ["hidden_size", "d_model"]:
                     UpperCAmelCase__    :							Optional[int]       		=     40
                  elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
                     UpperCAmelCase__    :							int       		=     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))








"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

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


A__       :			Union[str, Any]=						logging.get_logger(__name__)

A__       :			Dict=						{
    """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/config.json""",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}
class  __lowerCamelCase     (	_a	):
   a   :					Optional[int]			    ="""rembert"""

   def __init__(       self			,					snake_case_=25_0300			,					snake_case_=1152			,					snake_case_=32			,					snake_case_=18			,					snake_case_=256			,					snake_case_=1664			,					snake_case_=4608			,					snake_case_="gelu"			,					snake_case_=0.0			,					snake_case_=0.0			,					snake_case_=0.1			,					snake_case_=512			,					snake_case_=2			,					snake_case_=0.02			,					snake_case_=1E-12			,					snake_case_=True			,					snake_case_=0			,					snake_case_=312			,					snake_case_=313			,					**snake_case_			,					)		->							str:
       super().__init__(pad_token_id=snake_case_			,					bos_token_id=snake_case_			,					eos_token_id=snake_case_			,					**snake_case_   )

       UpperCamelCase__								=     vocab_size
       UpperCamelCase__								=     input_embedding_size
       UpperCamelCase__								=     output_embedding_size
       UpperCamelCase__								=     max_position_embeddings
       UpperCamelCase__								=     hidden_size
       UpperCamelCase__								=     num_hidden_layers
       UpperCamelCase__								=     num_attention_heads
       UpperCamelCase__								=     intermediate_size
       UpperCamelCase__								=     hidden_act
       UpperCamelCase__								=     hidden_dropout_prob
       UpperCamelCase__								=     attention_probs_dropout_prob
       UpperCamelCase__								=     classifier_dropout_prob
       UpperCamelCase__								=     initializer_range
       UpperCamelCase__								=     type_vocab_size
       UpperCamelCase__								=     layer_norm_eps
       UpperCamelCase__								=     use_cache
       UpperCamelCase__								=     False







class  __lowerCamelCase     (	_a	):

   @property
   def     SCREAMING_SNAKE_CASE__			(       self   )		->							Mapping[str, Mapping[int, str]]:
       if self.task == "multiple-choice":
           UpperCamelCase__								=     {0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
           UpperCamelCase__								=     {0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
               ('token_type_ids', dynamic_axis),
           ]   )







   @property
   def     SCREAMING_SNAKE_CASE__			(       self   )		->							float:
       return 1E-4




