code: from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  lowercase__    :       Union[str, Any]						=			logging.get_logger(__name__)
  
  lowercase__    :       Optional[int]						=			{
      '''flaubert/flaubert_small_cased''': '''https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json''',
      '''flaubert/flaubert_base_uncased''': '''https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json''',
      '''flaubert/flaubert_base_cased''': '''https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json''',
      '''flaubert/flaubert_large_cased''': '''https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json''',
  }
  
  
  
  
  class      lowercase_						(						lowerCAmelCase__		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      List[Any]     =       """flaubert"""
  	UpperCAmelCase_						:      Union[str, Any]     =       {
  	    """hidden_size""": """emb_dim""",
  	    """num_attention_heads""": """n_heads""",
  	    """num_hidden_layers""": """n_layers""",
  	    """n_words""": """vocab_size""",  # For backward compatibility
  	}
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=30145	,    __SCREAMING_SNAKE_CASE=2048	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=16	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=1	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=512	,    __SCREAMING_SNAKE_CASE=2048**-0.5	,    __SCREAMING_SNAKE_CASE=1e-12	,    __SCREAMING_SNAKE_CASE=0.0_2	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE=1	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=3	,    __SCREAMING_SNAKE_CASE=5	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE="first"	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=None	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=5	,    __SCREAMING_SNAKE_CASE=5	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=0	,    **__SCREAMING_SNAKE_CASE	,    )		->Union[str, Any]:
  								lowerCAmelCase				=	pre_norm
  								lowerCAmelCase				=	layerdrop
  								lowerCAmelCase				=	vocab_size
  								lowerCAmelCase				=	emb_dim
  								lowerCAmelCase				=	n_layers
  								lowerCAmelCase				=	n_heads
  								lowerCAmelCase				=	dropout
  								lowerCAmelCase				=	attention_dropout
  								lowerCAmelCase				=	gelu_activation
  								lowerCAmelCase				=	sinusoidal_embeddings
  								lowerCAmelCase				=	causal
  								lowerCAmelCase				=	asm
  								lowerCAmelCase				=	n_langs
  								lowerCAmelCase				=	use_lang_emb
  								lowerCAmelCase				=	layer_norm_eps
  								lowerCAmelCase				=	bos_index
  								lowerCAmelCase				=	eos_index
  								lowerCAmelCase				=	pad_index
  								lowerCAmelCase				=	unk_index
  								lowerCAmelCase				=	mask_index
  								lowerCAmelCase				=	is_encoder
  								lowerCAmelCase				=	max_position_embeddings
  								lowerCAmelCase				=	embed_init_std
  								lowerCAmelCase				=	init_std
  								lowerCAmelCase				=	summary_type
  								lowerCAmelCase				=	summary_use_proj
  								lowerCAmelCase				=	summary_activation
  								lowerCAmelCase				=	summary_proj_to_labels
  								lowerCAmelCase				=	summary_first_dropout
  								lowerCAmelCase				=	start_n_top
  								lowerCAmelCase				=	end_n_top
  								lowerCAmelCase				=	mask_token_id
  								lowerCAmelCase				=	lang_id
  
  								if "n_words" in kwargs:
  															lowerCAmelCase				=	kwargs['''n_words''']
  
  								super().__init__(pad_token_id=lowerCAmelCase_	,    bos_token_id=lowerCAmelCase_	,    **lowerCAmelCase_       )
  
  
  
  
  class      lowercase_						(						lowerCAmelCase__		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	@property
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->Mapping[str, Mapping[int, str]]:
  
  
  
  
  
  
  								if self.task == "multiple-choice":
  															lowerCAmelCase				=	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
  								else:
  															lowerCAmelCase				=	{0: '''batch''', 1: '''sequence'''}
  								return OrderedDict(
  								    [
  								        ('''input_ids''', dynamic_axis),
  								        ('''attention_mask''', dynamic_axis),
  								    ]       )
  
  
  
  
style_context: import glob
  import os
  
  from get_test_info import get_tester_classes
  
  
  if __name__ == "__main__":
  	lowercase__    :       List[Any]						=			[]
  
  	lowercase__    :       Optional[Any]						=			os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
  	lowercase__    :       Optional[int]						=			glob.glob(pattern)
  	# TODO: deal with TF/Flax too
  	lowercase__    :       Dict						=			[
  	    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:
  		lowercase__    :       Tuple						=			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:
  				lowercase__    :       Union[str, Any]						=			tester_class(parent=None)
  			except Exception:
  				continue
  			if hasattr(tester, '''get_config'''):
  				lowercase__    :       Union[str, Any]						=			tester.get_config()
  				for k, v in config.to_dict().items():
  					if isinstance(v, int):
  						lowercase__    :       int						=			None
  						if k in ["vocab_size"]:
  							lowercase__    :       Optional[int]						=			1_0_0
  						elif k in ["max_position_embeddings"]:
  							lowercase__    :       Union[str, Any]						=			1_2_8
  						elif k in ["hidden_size", "d_model"]:
  							lowercase__    :       Optional[Any]						=			4_0
  						elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
  							lowercase__    :       Dict						=			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))
  
  
  
  