





'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import is_detectrona_available, logging


A :			Union[str, Any]							   =      logging.get_logger(__name__)

A :			List[Any]							   =      {
    'layoutlmv2-base-uncased': 'https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json',
    'layoutlmv2-large-uncased': 'https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json',
    # See all LayoutLMv2 models at https://huggingface.co/models?filter=layoutlmv2
}

# soft dependency
if is_detectrona_available():
		import detectrona







class       lowerCamelCase       (    _A	):
					_SCREAMING_SNAKE_CASE				 =     "layoutlmv2"


					def __init__(       self						:	Tuple							,  __snake_case						:	Optional[int]=3_05_22							,  __snake_case						:	Optional[int]=7_68							,  __snake_case						:	Tuple=12							,  __snake_case						:	Optional[Any]=12							,  __snake_case						:	Dict=30_72							,  __snake_case						:	List[Any]="gelu"							,  __snake_case						:	Tuple=0.1							,  __snake_case						:	List[str]=0.1							,  __snake_case						:	Dict=5_12							,  __snake_case						:	Tuple=2							,  __snake_case						:	Optional[Any]=0.02							,  __snake_case						:	Any=1e-12							,  __snake_case						:	int=0							,  __snake_case						:	int=10_24							,  __snake_case						:	Optional[Any]=1_28							,  __snake_case						:	str=32							,  __snake_case						:	Optional[Any]=True							,  __snake_case						:	Union[str, Any]=2_56							,  __snake_case						:	List[str]=64							,  __snake_case						:	int=True							,  __snake_case						:	List[str]=[7, 7, 2_56]							,  __snake_case						:	Union[str, Any]=1_28							,  __snake_case						:	int=1_28							,  __snake_case						:	List[Any]=True							,  __snake_case						:	Any=True							,  __snake_case						:	Tuple=False							,  __snake_case						:	Optional[Any]=None							,  **__snake_case						:	Dict							,  ):





											'''simple docstring'''





											super().__init__(
											    vocab_size=__lowercase							,  hidden_size=__lowercase							,  num_hidden_layers=__lowercase							,  num_attention_heads=__lowercase							,  intermediate_size=__lowercase							,  hidden_act=__lowercase							,  hidden_dropout_prob=__lowercase							,  attention_probs_dropout_prob=__lowercase							,  max_position_embeddings=__lowercase							,  type_vocab_size=__lowercase							,  initializer_range=__lowercase							,  layer_norm_eps=__lowercase							,  pad_token_id=__lowercase							,  **__lowercase							,  )
											_snake_case: Tuple	       =		max_ad_position_embeddings
											_snake_case: Dict	       =		max_rel_pos
											_snake_case: Any	       =		rel_pos_bins
											_snake_case: List[Any]	       =		fast_qkv
											_snake_case: Optional[int]	       =		max_rel_ad_pos
											_snake_case: Tuple	       =		rel_ad_pos_bins
											_snake_case: Dict	       =		convert_sync_batchnorm
											_snake_case: Optional[Any]	       =		image_feature_pool_shape
											_snake_case: int	       =		coordinate_size
											_snake_case: Dict	       =		shape_size
											_snake_case: Any	       =		has_relative_attention_bias
											_snake_case: Union[str, Any]	       =		has_spatial_attention_bias
											_snake_case: List[str]	       =		has_visual_segment_embedding
											_snake_case: List[str]	       =		(
											    detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
											)


					@classmethod
					def  SCREAMING_SNAKE_CASE_		(       self						:	Tuple							):





											'''simple docstring'''





											return {
											    "MODEL.MASK_ON": True,
											    "MODEL.PIXEL_STD": [57.3_75, 57.1_20, 58.3_95],
											    "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
											    "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
											    "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [1_28], [2_56], [5_12]],
											    "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
											    "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 20_00,
											    "MODEL.RPN.PRE_NMS_TOPK_TEST": 10_00,
											    "MODEL.RPN.POST_NMS_TOPK_TRAIN": 10_00,
											    "MODEL.POST_NMS_TOPK_TEST": 10_00,
											    "MODEL.ROI_HEADS.NAME": "StandardROIHeads",
											    "MODEL.ROI_HEADS.NUM_CLASSES": 5,
											    "MODEL.ROI_HEADS.IN_FEATURES": ["p2", "p3", "p4", "p5"],
											    "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead",
											    "MODEL.ROI_BOX_HEAD.NUM_FC": 2,
											    "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 14,
											    "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
											    "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
											    "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
											    "MODEL.RESNETS.DEPTH": 1_01,
											    "MODEL.RESNETS.SIZES": [[32], [64], [1_28], [2_56], [5_12]],
											    "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
											    "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
											    "MODEL.RESNETS.NUM_GROUPS": 32,
											    "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
											    "MODEL.RESNETS.STRIDE_IN_1X1": False,
											}




					def  SCREAMING_SNAKE_CASE_		(       self						:	Union[str, Any]							):





											'''simple docstring'''





											_snake_case: Optional[int]	       =		detectrona.config.get_cfg()
											for k, v in self.detectrona_config_args.items():
																	_snake_case: Tuple	       =		k.split('.'							)
																	_snake_case: List[str]	       =		detectrona_config
																	for attribute in attributes[:-1]:
																							_snake_case: Optional[Any]	       =		getattr(__lowercase							,  __lowercase							)
																	setattr(__lowercase							,  attributes[-1]							,  __lowercase							)

											return detectrona_config












def        A__						(							SCREAMING_SNAKE_CASE_				,							SCREAMING_SNAKE_CASE_				,							SCREAMING_SNAKE_CASE_		) ->  Dict:
		assert b != 0, "This cannot accept modulo that is == 0"
		if n == 0:
				return 1

		if n % 2 == 1:
				return (bin_exp_mod(SCREAMING_SNAKE_CASE_				,							n - 1				,							SCREAMING_SNAKE_CASE_		) * a) % b

		lowerCamelCase :			Tuple    		=bin_exp_mod(SCREAMING_SNAKE_CASE_				,							n / 2				,							SCREAMING_SNAKE_CASE_		)
		return (r * r) % b


if __name__ == "__main__":
				try:
								snake_case_				=      int(input('''Enter Base : ''').strip())
								snake_case_				=      int(input('''Enter Power : ''').strip())
								snake_case_				=      int(input('''Enter Modulo : ''').strip())
				except ValueError:
								print('''Invalid literal for integer''')

				print(bin_exp_mod(BASE, POWER, MODULO))

