import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


_UpperCAmelCase	:     Any		       = {
    """facebook/mask2former-swin-small-coco-instance""": (
        """https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json"""
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

_UpperCAmelCase	:     Optional[Any]		       = logging.get_logger(__name__)







class 				lowercase       ( lowercase_    ):
				__SCREAMING_SNAKE_CASE      :				Any     =    '''mask2former'''
				__SCREAMING_SNAKE_CASE      :				List[Any]     =    ['''swin''']
				__SCREAMING_SNAKE_CASE      :				Tuple     =    {'''hidden_size''': '''hidden_dim'''}




				def __init__(      self   ,     snake_case = None   ,     snake_case = 256   ,     snake_case = 256   ,     snake_case = 256   ,     snake_case = 1024   ,     snake_case = "relu"   ,     snake_case = 6   ,     snake_case = 10   ,     snake_case = 8   ,     snake_case = 0.0   ,     snake_case = 2048   ,     snake_case = False   ,     snake_case = False   ,     snake_case = 4   ,     snake_case = 255   ,     snake_case = 100   ,     snake_case = 0.1   ,     snake_case = 2.0   ,     snake_case = 5.0   ,     snake_case = 5.0   ,     snake_case = 1_2544   ,     snake_case = 3.0   ,     snake_case = 0.75   ,     snake_case = 0.02   ,     snake_case = 1.0   ,     snake_case = True   ,     snake_case = [4, 8, 16, 32]   ,     snake_case = None   ,     **snake_case   ,     ):
											if backbone_config is None:
																		logger.info('`backbone_config` is `None`. Initializing the config with the default `Swin` backbone.' )
																		snake_case_           =					CONFIG_MAPPING['swin'](
																		    image_size=224   ,     in_channels=3   ,     patch_size=4   ,     embed_dim=96   ,     depths=[2, 2, 18, 2]   ,     num_heads=[3, 6, 12, 24]   ,     window_size=7   ,     drop_path_rate=0.3   ,     use_absolute_embeddings=snake_case   ,     out_features=['stage1', 'stage2', 'stage3', 'stage4']   ,     )

											if isinstance(snake_case   ,     snake_case ):
																		snake_case_           =					backbone_config.pop('model_type' )
																		snake_case_           =					CONFIG_MAPPING[backbone_model_type]
																		snake_case_           =					config_class.from_dict(snake_case )

											# verify that the backbone is supported
											if backbone_config.model_type not in self.backbones_supported:
																		logger.warning_once(
																		    F'''Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. '''
																		    F'''Supported model types: {",".join(self.backbones_supported )}''' )

											snake_case_           =					backbone_config
											snake_case_           =					feature_size
											snake_case_           =					mask_feature_size
											snake_case_           =					hidden_dim
											snake_case_           =					encoder_feedforward_dim
											snake_case_           =					activation_function
											snake_case_           =					encoder_layers
											snake_case_           =					decoder_layers
											snake_case_           =					num_attention_heads
											snake_case_           =					dropout
											snake_case_           =					dim_feedforward
											snake_case_           =					pre_norm
											snake_case_           =					enforce_input_projection
											snake_case_           =					common_stride
											snake_case_           =					ignore_value
											snake_case_           =					num_queries
											snake_case_           =					no_object_weight
											snake_case_           =					class_weight
											snake_case_           =					mask_weight
											snake_case_           =					dice_weight
											snake_case_           =					train_num_points
											snake_case_           =					oversample_ratio
											snake_case_           =					importance_sample_ratio
											snake_case_           =					init_std
											snake_case_           =					init_xavier_std
											snake_case_           =					use_auxiliary_loss
											snake_case_           =					feature_strides
											snake_case_           =					output_auxiliary_logits
											snake_case_           =					decoder_layers

											super().__init__(**snake_case )




				@classmethod
				def 					a							(      cls   ,     snake_case   ,     **snake_case ):
											return cls(
											    backbone_config=snake_case   ,     **snake_case   ,     )




				def 					a							(      self ):
											snake_case_           =					copy.deepcopy(self.__dict__ )
											snake_case_           =					self.backbone_config.to_dict()
											snake_case_           =					self.__class__.model_type
											return output







def       __lowerCamelCase			(				UpperCamelCase__ = 50000000   ):







							'''simple docstring'''






							snake_case_           =					set()
							snake_case_           =					int((limit - 24) ** (1 / 2)   )

							snake_case_           =					set(range(3     ,							prime_square_limit + 1     ,							2   )   )
							primes.add(2   )
							for p in range(3     ,							prime_square_limit + 1     ,							2   ):
														if p not in primes:
																					continue
														primes.difference_update(set(range(p * p     ,							prime_square_limit + 1     ,							UpperCamelCase__   )   )   )

							for primea in primes:
														snake_case_           =					primea * primea
														for primea in primes:
																					snake_case_           =					primea * primea * primea
																					if square + cube >= limit - 16:
																												break
																					for primea in primes:
																												snake_case_           =					primea * primea * primea * primea
																												snake_case_           =					square + cube + tetr
																												if total >= limit:
																																			break
																												ret.add(UpperCamelCase__   )

							return len(UpperCamelCase__   )


if __name__ == "__main__":
					print(F'''{solution() = }''')




