


from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase						=		logging.get_logger(__name__)

lowerCamelCase						=		{
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}





class 					_a							(				a_):
	_a  :  Optional[int]          =							'''distilbert'''
	_a  :  Optional[int]          =							{
	    '''hidden_size''': '''dim''',
	    '''num_attention_heads''': '''n_heads''',
	    '''num_hidden_layers''': '''n_layers''',
	}




	def __init__(					self						:		Optional[Any]		,					_SCREAMING_SNAKE_CASE						:		str=3_0522		,					_SCREAMING_SNAKE_CASE						:		str=512		,					_SCREAMING_SNAKE_CASE						:		str=False		,					_SCREAMING_SNAKE_CASE						:		str=6		,					_SCREAMING_SNAKE_CASE						:		int=12		,					_SCREAMING_SNAKE_CASE						:		Optional[int]=768		,					_SCREAMING_SNAKE_CASE						:		str=4 * 768		,					_SCREAMING_SNAKE_CASE						:		Any=0.1		,					_SCREAMING_SNAKE_CASE						:		Optional[int]=0.1		,					_SCREAMING_SNAKE_CASE						:		Dict="gelu"		,					_SCREAMING_SNAKE_CASE						:		str=0.02		,					_SCREAMING_SNAKE_CASE						:		Optional[Any]=0.1		,					_SCREAMING_SNAKE_CASE						:		List[str]=0.2		,					_SCREAMING_SNAKE_CASE						:		Optional[Any]=0		,					**_SCREAMING_SNAKE_CASE						:		int		,					)->       int:
			lowerCAmelCase__   :			str         =					vocab_size
			lowerCAmelCase__   :			Optional[int]         =					max_position_embeddings
			lowerCAmelCase__   :			int         =					sinusoidal_pos_embds
			lowerCAmelCase__   :			List[Any]         =					n_layers
			lowerCAmelCase__   :			str         =					n_heads
			lowerCAmelCase__   :			List[Any]         =					dim
			lowerCAmelCase__   :			int         =					hidden_dim
			lowerCAmelCase__   :			Optional[int]         =					dropout
			lowerCAmelCase__   :			Any         =					attention_dropout
			lowerCAmelCase__   :			Tuple         =					activation
			lowerCAmelCase__   :			Tuple         =					initializer_range
			lowerCAmelCase__   :			List[str]         =					qa_dropout
			lowerCAmelCase__   :			Optional[int]         =					seq_classif_dropout
			super().__init__(**_A		,					pad_token_id=_A		)





class 					_a							(				a_):




	@property
	def 							UpperCAmelCase__(					self						:		Optional[Any]		)->       Dict:







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











def 						__SCREAMING_SNAKE_CASE  (				UpperCamelCase__ )  ->				list[int]:







			'''simple docstring'''

			if length <= 0 or not isinstance(UpperCamelCase__			,			UpperCamelCase__ ):
						raise ValueError('''Length must be a positive integer.''' )
			return [n * (2 * n - 1) for n in range(UpperCamelCase__ )]


if __name__ == "__main__":
				print(hexagonal_numbers(length=5))
				print(hexagonal_numbers(length=10))



