from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE		:     List[Any]         =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:     Any         =	{
    "camembert-base": "https://huggingface.co/camembert-base/resolve/main/config.json",
    "umberto-commoncrawl-cased-v1": (
        "https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"
    ),
    "umberto-wikipedia-uncased-v1": (
        "https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"
    ),
}

class        UpperCamelCase						(				__a				):
						a__		:int      =			'''camembert'''





						def __init__(self			,     __UpperCamelCase=30_522			,     __UpperCamelCase=768			,     __UpperCamelCase=12			,     __UpperCamelCase=12			,     __UpperCamelCase=3_072			,     __UpperCamelCase="gelu"			,     __UpperCamelCase=0.1			,     __UpperCamelCase=0.1			,     __UpperCamelCase=512			,     __UpperCamelCase=2			,     __UpperCamelCase=0.02			,     __UpperCamelCase=1E-1_2			,     __UpperCamelCase=1			,     __UpperCamelCase=0			,     __UpperCamelCase=2			,     __UpperCamelCase="absolute"			,     __UpperCamelCase=True			,     __UpperCamelCase=None			,     **__UpperCamelCase			,     )				->				Union[str, Any]:
												super().__init__(pad_token_id=__UpperCamelCase			,     bos_token_id=__UpperCamelCase			,     eos_token_id=__UpperCamelCase			,     **__UpperCamelCase						)

												UpperCamelCase_		:							List[Any]  =		vocab_size
												UpperCamelCase_		:							int  =		hidden_size
												UpperCamelCase_		:							int  =		num_hidden_layers
												UpperCamelCase_		:							List[str]  =		num_attention_heads
												UpperCamelCase_		:							str  =		hidden_act
												UpperCamelCase_		:							int  =		intermediate_size
												UpperCamelCase_		:							Dict  =		hidden_dropout_prob
												UpperCamelCase_		:							Any  =		attention_probs_dropout_prob
												UpperCamelCase_		:							str  =		max_position_embeddings
												UpperCamelCase_		:							str  =		type_vocab_size
												UpperCamelCase_		:							str  =		initializer_range
												UpperCamelCase_		:							Dict  =		layer_norm_eps
												UpperCamelCase_		:							str  =		position_embedding_type
												UpperCamelCase_		:							Union[str, Any]  =		use_cache
												UpperCamelCase_		:							int  =		classifier_dropout


class        UpperCamelCase						(				__a				):





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







import numpy as np






def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				np.array			):
						return (2 / (1 + np.exp(-2 * vector			))) - 1


if __name__ == "__main__":
	import doctest

	doctest.testmod()






