






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


a 			=							logging.get_logger(__name__)

a 			=							{
    '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 							__snake_case(       _snake_case   ):
 lowercase			:							int		   =		'''layoutlmv2'''



 def __init__(						self : List[str]			,		UpperCAmelCase__ : List[Any]=30_522			,		UpperCAmelCase__ : List[str]=768			,		UpperCAmelCase__ : Union[str, Any]=12			,		UpperCAmelCase__ : Optional[int]=12			,		UpperCAmelCase__ : Optional[int]=3_072			,		UpperCAmelCase__ : List[Any]="gelu"			,		UpperCAmelCase__ : List[str]=0.1			,		UpperCAmelCase__ : int=0.1			,		UpperCAmelCase__ : str=512			,		UpperCAmelCase__ : str=2			,		UpperCAmelCase__ : Any=0.02			,		UpperCAmelCase__ : str=1e-12			,		UpperCAmelCase__ : str=0			,		UpperCAmelCase__ : Any=1_024			,		UpperCAmelCase__ : List[Any]=128			,		UpperCAmelCase__ : Union[str, Any]=32			,		UpperCAmelCase__ : int=True			,		UpperCAmelCase__ : Optional[Any]=256			,		UpperCAmelCase__ : Optional[Any]=64			,		UpperCAmelCase__ : Optional[int]=True			,		UpperCAmelCase__ : int=[7, 7, 256]			,		UpperCAmelCase__ : Dict=128			,		UpperCAmelCase__ : List[Any]=128			,		UpperCAmelCase__ : Any=True			,		UpperCAmelCase__ : List[Any]=True			,		UpperCAmelCase__ : int=False			,		UpperCAmelCase__ : Union[str, Any]=None			,		**UpperCAmelCase__ : Optional[int]			,		):

    """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__			,		)
    lowercase__    :						List[str]       =			max_ad_position_embeddings
    lowercase__    :						int       =			max_rel_pos
    lowercase__    :						Any       =			rel_pos_bins
    lowercase__    :						Dict       =			fast_qkv
    lowercase__    :						Union[str, Any]       =			max_rel_ad_pos
    lowercase__    :						Tuple       =			rel_ad_pos_bins
    lowercase__    :						Dict       =			convert_sync_batchnorm
    lowercase__    :						Any       =			image_feature_pool_shape
    lowercase__    :						Optional[int]       =			coordinate_size
    lowercase__    :						Union[str, Any]       =			shape_size
    lowercase__    :						str       =			has_relative_attention_bias
    lowercase__    :						Any       =			has_spatial_attention_bias
    lowercase__    :						int       =			has_visual_segment_embedding
    lowercase__    :						Union[str, Any]       =			(
        detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
    )



 @classmethod
 def     UpperCAmelCase     (						self : Optional[int]						):

    """simple docstring"""






    return {
        "MODEL.MASK_ON": True,
        "MODEL.PIXEL_STD": [57.375, 57.120, 58.395],
        "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
        "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
        "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [128], [256], [512]],
        "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
        "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2_000,
        "MODEL.RPN.PRE_NMS_TOPK_TEST": 1_000,
        "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1_000,
        "MODEL.POST_NMS_TOPK_TEST": 1_000,
        "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": 101,
        "MODEL.RESNETS.SIZES": [[32], [64], [128], [256], [512]],
        "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     UpperCAmelCase     (						self : Dict						):

    """simple docstring"""






    lowercase__    :						Any       =			detectrona.config.get_cfg()
    for k, v in self.detectrona_config_args.items():
       lowercase__    :						Any       =			k.split("""."""						)
       lowercase__    :						str       =			detectrona_config
       for attribute in attributes[:-1]:
          lowercase__    :						str       =			getattr(lowercase__			,		lowercase__						)
       setattr(lowercase__			,		attributes[-1]			,		lowercase__						)

    return detectrona_config







from __future__ import annotations

# Define the Gravitational Constant G and the function
__magic_name__       =     6.6743E-11  # unit of G : m^3 * kg^-1 * s^-2





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					lowercase						   =       mass_a * mass_a

					if (force, mass_a, mass_a, distance).count(0				) != 1:
										raise ValueError('One and only one argument must be 0'				)
					if force < 0:
										raise ValueError('Gravitational force can not be negative'				)
					if distance < 0:
										raise ValueError('Distance can not be negative'				)
					if mass_a < 0 or mass_a < 0:
										raise ValueError('Mass can not be negative'				)
					if force == 0:
										lowercase						   =       GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
										return {"force": force}
					elif mass_a == 0:
										lowercase						   =       (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
										return {"mass_1": mass_a}
					elif mass_a == 0:
										lowercase						   =       (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
										return {"mass_2": mass_a}
					elif distance == 0:
										lowercase						   =       (GRAVITATIONAL_CONSTANT * product_of_mass / (force)) ** 0.5
										return {"distance": distance}
					raise ValueError('One and only one argument must be 0'				)


# Run doctest
if __name__ == "__main__":
		import doctest

		doctest.testmod()






