



"""simple docstring"""


import math

def 			_lowerCAmelCase				(       lowercase_						):
						assert isinstance(lowercase_		,     lowercase_						) and (
						    number >= 0
						), "'number' must been an int and positive"

						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or not number % 2:
												# Negatives, 0, 1 and all even numbers are not primes
												return False

						UpperCAmelCase					=			range(3		,     int(math.sqrt(lowercase_						) + 1						)		,     2						)
						return not any(not number % i for i in odd_numbers						)






def 			_lowerCAmelCase				(       lowercase_		,     lowercase_=1		,     **lowercase_						):
						UpperCAmelCase					=			factor * value
						UpperCAmelCase					=			value

						while not is_prime(lowercase_						):
												value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

						if value == first_value_val:
												return next_prime(value + 1		,     **lowercase_						)
						return value










"""simple docstring"""


import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig


snake_case_    					=	{
    """facebook/maskformer-swin-base-ade""": (
        """https://huggingface.co/facebook/maskformer-swin-base-ade/blob/main/config.json"""
    )
    # See all MaskFormer models at https://huggingface.co/models?filter=maskformer
}

snake_case_    					=	logging.get_logger(__name__)







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""
						__UpperCamelCase		    =							"""maskformer"""
						__UpperCamelCase		    =							{"""hidden_size""": """mask_feature_size"""}
						__UpperCamelCase		    =							["""resnet""", """swin"""]
						__UpperCamelCase		    =							["""detr"""]






						def __init__( self			:Dict       ,  lowercase_			:int = 2_56       ,  lowercase_			:int = 2_56       ,  lowercase_			:float = 0.1       ,  lowercase_			:bool = False       ,  lowercase_			:Optional[Dict] = None       ,  lowercase_			:Optional[Dict] = None       ,  lowercase_			:float = 0.02       ,  lowercase_			:float = 1.0       ,  lowercase_			:float = 1.0       ,  lowercase_			:float = 1.0       ,  lowercase_			:float = 20.0       ,  lowercase_			:Optional[bool] = None       ,  **lowercase_			:List[str]       ,  )    ->      Optional[int]:
												if backbone_config is None:
																		# fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
																		UpperCAmelCase					=			SwinConfig(
																		    image_size=3_84       ,  in_channels=3       ,  patch_size=4       ,  embed_dim=1_28       ,  depths=[2, 2, 18, 2]       ,  num_heads=[4, 8, 16, 32]       ,  window_size=12       ,  drop_path_rate=0.3       ,  out_features=['stage1', 'stage2', 'stage3', 'stage4']       ,  )

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

												# 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 MaskFormer. """
																		    f"""Supported model types: {','.join(self.backbones_supported )}""" )

												if decoder_config is None:
																		# fall back to https://huggingface.co/facebook/detr-resnet-50
																		UpperCAmelCase					=			DetrConfig()
												else:
																		# verify that the decoder is supported
																		UpperCAmelCase					=			(
																		    decoder_config.pop('model_type' ) if isinstance(lowercase_       ,  lowercase_ ) else decoder_config.model_type
																		)
																		if decoder_type not in self.decoders_supported:
																								raise ValueError(
																								    f"""Transformer Decoder {decoder_type} not supported, please use one of"""
																								    f""" {','.join(self.decoders_supported )}""" )
																		if isinstance(lowercase_       ,  lowercase_ ):
																								UpperCAmelCase					=			CONFIG_MAPPING[decoder_type]
																								UpperCAmelCase					=			config_class.from_dict(lowercase_ )

												UpperCAmelCase					=			backbone_config
												UpperCAmelCase					=			decoder_config
												# main feature dimension for the model
												UpperCAmelCase					=			fpn_feature_size
												UpperCAmelCase					=			mask_feature_size
												# initializer
												UpperCAmelCase					=			init_std
												UpperCAmelCase					=			init_xavier_std
												# Hungarian matcher && loss
												UpperCAmelCase					=			cross_entropy_weight
												UpperCAmelCase					=			dice_weight
												UpperCAmelCase					=			mask_weight
												UpperCAmelCase					=			use_auxiliary_loss
												UpperCAmelCase					=			no_object_weight
												UpperCAmelCase					=			output_auxiliary_logits

												UpperCAmelCase					=			self.decoder_config.encoder_attention_heads
												UpperCAmelCase					=			self.decoder_config.num_hidden_layers
												super().__init__(**lowercase_ )






						@classmethod
						def      UpperCAmelCase__					( cls			:int       ,  lowercase_			:PretrainedConfig       ,  lowercase_			:PretrainedConfig       ,  **lowercase_			:int )    ->      List[Any]:
												return cls(
												    backbone_config=lowercase_       ,  decoder_config=lowercase_       ,  **lowercase_       ,  )






						def      UpperCAmelCase__					( self			:Tuple )    ->      Dict[str, any]:
												UpperCAmelCase					=			copy.deepcopy(self.__dict__ )
												UpperCAmelCase					=			self.backbone_config.to_dict()
												UpperCAmelCase					=			self.decoder_config.to_dict()
												UpperCAmelCase					=			self.__class__.model_type
												return output





