





'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

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


snake_case_  :							int            =	logging.get_logger(__name__)

snake_case_  :							List[Any]            =	{
    "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        __a   (lowerCamelCase  ):
							__a       : List[str]          =							"flaubert"
							__a       : Dict          =							{
							    "hidden_size": "emb_dim",
							    "num_attention_heads": "n_heads",
							    "num_hidden_layers": "n_layers",
							    "n_words": "vocab_size",  # For backward compatibility
							}

							def __init__(				self				:  Tuple							,  __magic_name__				:  Optional[int]=False							,  __magic_name__				:  List[Any]=0.0							,  __magic_name__				:  str=3_01_45							,  __magic_name__				:  str=20_48							,  __magic_name__				:  Union[str, Any]=12							,  __magic_name__				:  str=16							,  __magic_name__				:  Optional[Any]=0.1							,  __magic_name__				:  Tuple=0.1							,  __magic_name__				:  Optional[int]=True							,  __magic_name__				:  List[Any]=False							,  __magic_name__				:  Tuple=False							,  __magic_name__				:  List[Any]=False							,  __magic_name__				:  List[Any]=1							,  __magic_name__				:  str=True							,  __magic_name__				:  Optional[Any]=5_12							,  __magic_name__				:  Optional[int]=20_48**-0.5							,  __magic_name__				:  str=1E-12							,  __magic_name__				:  Optional[int]=0.0_2							,  __magic_name__				:  Optional[Any]=0							,  __magic_name__				:  int=1							,  __magic_name__				:  Optional[int]=2							,  __magic_name__				:  int=3							,  __magic_name__				:  Tuple=5							,  __magic_name__				:  Optional[Any]=True							,  __magic_name__				:  str="first"							,  __magic_name__				:  int=True							,  __magic_name__				:  Any=None							,  __magic_name__				:  str=True							,  __magic_name__				:  Dict=0.1							,  __magic_name__				:  Tuple=5							,  __magic_name__				:  Dict=5							,  __magic_name__				:  Optional[int]=0							,  __magic_name__				:  List[Any]=0							,  __magic_name__				:  Optional[int]=2							,  __magic_name__				:  List[str]=0							,  **__magic_name__				:  Union[str, Any]							,  )       ->							Dict:







													"""simple docstring"""
													UpperCAmelCase_      :   Union[str, Any]      =	pre_norm
													UpperCAmelCase_      :   int      =	layerdrop
													UpperCAmelCase_      :   Union[str, Any]      =	vocab_size
													UpperCAmelCase_      :   Tuple      =	emb_dim
													UpperCAmelCase_      :   Tuple      =	n_layers
													UpperCAmelCase_      :   Optional[int]      =	n_heads
													UpperCAmelCase_      :   Dict      =	dropout
													UpperCAmelCase_      :   int      =	attention_dropout
													UpperCAmelCase_      :   List[str]      =	gelu_activation
													UpperCAmelCase_      :   Dict      =	sinusoidal_embeddings
													UpperCAmelCase_      :   int      =	causal
													UpperCAmelCase_      :   Any      =	asm
													UpperCAmelCase_      :   Union[str, Any]      =	n_langs
													UpperCAmelCase_      :   Any      =	use_lang_emb
													UpperCAmelCase_      :   str      =	layer_norm_eps
													UpperCAmelCase_      :   Optional[int]      =	bos_index
													UpperCAmelCase_      :   Optional[Any]      =	eos_index
													UpperCAmelCase_      :   Optional[Any]      =	pad_index
													UpperCAmelCase_      :   str      =	unk_index
													UpperCAmelCase_      :   str      =	mask_index
													UpperCAmelCase_      :   Dict      =	is_encoder
													UpperCAmelCase_      :   int      =	max_position_embeddings
													UpperCAmelCase_      :   List[str]      =	embed_init_std
													UpperCAmelCase_      :   str      =	init_std
													UpperCAmelCase_      :   Tuple      =	summary_type
													UpperCAmelCase_      :   Union[str, Any]      =	summary_use_proj
													UpperCAmelCase_      :   List[str]      =	summary_activation
													UpperCAmelCase_      :   Any      =	summary_proj_to_labels
													UpperCAmelCase_      :   int      =	summary_first_dropout
													UpperCAmelCase_      :   List[Any]      =	start_n_top
													UpperCAmelCase_      :   Union[str, Any]      =	end_n_top
													UpperCAmelCase_      :   Tuple      =	mask_token_id
													UpperCAmelCase_      :   str      =	lang_id

													if "n_words" in kwargs:
																			UpperCAmelCase_      :   Union[str, Any]      =	kwargs['''n_words''']

													super().__init__(pad_token_id=__magic_name__							,  bos_token_id=__magic_name__							,  **__magic_name__ )





class        __a   (lowerCamelCase  ):

							@property
							def      UpperCAmelCase__						(				self				:  Dict )       ->							Mapping[str, Mapping[int, str]]:







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












'''simple docstring'''







from __future__ import annotations





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      list[int | float] )			->						int | float:
						if len(SCREAMING_SNAKE_CASE__ ) == 0:
												raise ValueError('''find_min() arg is an empty sequence''' )
						UpperCAmelCase_      :   Optional[int]      =	nums[0]
						for num in nums:
												UpperCAmelCase_      :   Tuple      =	min(SCREAMING_SNAKE_CASE__,      SCREAMING_SNAKE_CASE__ )
						return min_num


if __name__ == "__main__":
					import doctest

					doctest.testmod(verbose=True)





