






from collections import OrderedDict
from typing import Mapping

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


__lowercase       :Tuple       =  logging.get_logger(__name__)

__lowercase       :List[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    _a     (				SCREAMING_SNAKE_CASE_							):






							"""simple docstring"""

							snake_case_							 =						"camembert"

							def __init__(      self				:     int							,	a				:     Dict=3_05_22							,	a				:     Union[str, Any]=7_68							,	a				:     Union[str, Any]=12							,	a				:     int=12							,	a				:     Any=30_72							,	a				:     Union[str, Any]="gelu"							,	a				:     Union[str, Any]=0.1							,	a				:     Union[str, Any]=0.1							,	a				:     str=5_12							,	a				:     Tuple=2							,	a				:     str=0.02							,	a				:     Tuple=1E-12							,	a				:     str=1							,	a				:     Optional[int]=0							,	a				:     str=2							,	a				:     Union[str, Any]="absolute"							,	a				:     Any=True							,	a				:     int=None							,	**a				:     Any							,	)	->Optional[int]:
													super().__init__(pad_token_id=UpperCamelCase__							,	bos_token_id=UpperCamelCase__							,	eos_token_id=UpperCamelCase__							,	**UpperCamelCase__    )

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







class    _a     (				SCREAMING_SNAKE_CASE_							):






							"""simple docstring"""

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






from __future__ import annotations







def       UpperCAmelCase							(     _lowerCamelCase      :  list[int]			,   _lowerCamelCase      :  int     ):





						'''simple docstring'''


						if len(_lowerCamelCase     ) < k or k < 0:
												raise ValueError("Invalid Input"     )
						SCREAMING_SNAKE_CASE__     :				int   =					sum(array[:k]     )
						for i in range(len(_lowerCamelCase     ) - k     ):
												SCREAMING_SNAKE_CASE__     :				str   =					current_sum - array[i] + array[i + k]
												SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					max(_lowerCamelCase			,   _lowerCamelCase     )
						return max_sum


if __name__ == "__main__":
				from doctest import testmod
				from random import randint

				testmod()
				__lowercase       :List[str]       =  [randint(-1_000, 1_000) for i in range(100)]
				__lowercase       :Any       =  randint(0, 110)
				print(f"The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}")