


"""simple docstring"""




import copy
from typing import Dict, List, Optional

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


lowercase_			     =  {
    "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
}

lowercase_			     =  logging.get_logger(__name__)
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		__UpperCAmelCase		:			Dict										=				'mask2former'
		__UpperCAmelCase		:			Dict										=				['swin']
		__UpperCAmelCase		:			Dict										=				{'hidden_size': 'hidden_dim'}

		def __init__(  self							, _a = None							, _a = 256							, _a = 256							, _a = 256							, _a = 1_024							, _a = "relu"							, _a = 6							, _a = 10							, _a = 8							, _a = 0.0							, _a = 2_048							, _a = False							, _a = False							, _a = 4							, _a = 255							, _a = 100							, _a = 0.1							, _a = 2.0							, _a = 5.0							, _a = 5.0							, _a = 12_544							, _a = 3.0							, _a = 0.75							, _a = 0.02							, _a = 1.0							, _a = True							, _a = [4, 8, 16, 32]							, _a = None							, **_a							, ):
				if backbone_config is None:
						logger.info('''`backbone_config` is `None`. Initializing the config with the default `Swin` backbone.'''      )
						__a           =			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=_a							, out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']							, )

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

				# 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      )}'''      )

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

				super().__init__(**_a      )

		@classmethod
		def 			__UpperCAmelCase       (  cls							, _a							, **_a      ):
				return cls(
				    backbone_config=_a							, **_a							, )





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










"""simple docstring"""




def        lowercase							(		lowerCAmelCase__ :     int    ,					lowerCAmelCase__ :     list			) ->      List[Any]:
		_enforce_args(lowerCAmelCase__    ,					lowerCAmelCase__			)
		if n == 0:
				return 0
		__a           =			float('''-inf'''			)
		for i in range(1    ,					n + 1			):
				__a           =			max(
				    lowerCAmelCase__    ,					prices[i - 1] + naive_cut_rod_recursive(n - i    ,					lowerCAmelCase__			)			)

		return max_revue

def        lowercase							(		lowerCAmelCase__ :     int    ,					lowerCAmelCase__ :     list			) ->      List[str]:
		_enforce_args(lowerCAmelCase__    ,					lowerCAmelCase__			)
		__a           =			[float('''-inf'''			) for _ in range(n + 1			)]
		return _top_down_cut_rod_recursive(lowerCAmelCase__    ,					lowerCAmelCase__    ,					lowerCAmelCase__			)

def        lowercase							(		lowerCAmelCase__ :     int    ,					lowerCAmelCase__ :     list    ,					lowerCAmelCase__ :     list			) ->      Union[str, Any]:
		if max_rev[n] >= 0:
				return max_rev[n]
		elif n == 0:
				return 0
		else:
				__a           =			float('''-inf'''			)
				for i in range(1    ,					n + 1			):
						__a           =			max(
						    lowerCAmelCase__    ,					prices[i - 1] + _top_down_cut_rod_recursive(n - i    ,					lowerCAmelCase__    ,					lowerCAmelCase__			)    ,					)

				__a           =			max_revenue

		return max_rev[n]

def        lowercase							(		lowerCAmelCase__ :     int    ,					lowerCAmelCase__ :     list			) ->      Dict:
		_enforce_args(lowerCAmelCase__    ,					lowerCAmelCase__			)

		# length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
		# length 0.
		__a           =			[float('''-inf'''			) for _ in range(n + 1			)]
		__a           =			0

		for i in range(1    ,					n + 1			):
				__a           =			max_rev[i]
				for j in range(1    ,					i + 1			):
						__a           =			max(lowerCAmelCase__    ,					prices[j - 1] + max_rev[i - j]			)

				__a           =			max_revenue_i

		return max_rev[n]

def        lowercase							(		lowerCAmelCase__ :     int    ,					lowerCAmelCase__ :     list			) ->      str:
		if n < 0:
				__a           =			f'''n must be greater than or equal to 0. Got n = {n}'''
				raise ValueError(lowerCAmelCase__			)

		if n > len(lowerCAmelCase__			):
				__a           =			(
				    '''Each integral piece of rod must have a corresponding price. '''
				    f'''Got n = {n} but length of prices = {len(lowerCAmelCase__			)}'''
				)
				raise ValueError(lowerCAmelCase__			)

def        lowercase							(		) ->      int:
		__a           =			[6, 10, 12, 15, 20, 23]
		__a           =			len(lowerCAmelCase__			)

		# the best revenue comes from cutting the rod into 6 pieces, each
		# of length 1 resulting in a revenue of 6 * 6 = 36.
		__a           =			36

		__a           =			top_down_cut_rod(lowerCAmelCase__    ,					lowerCAmelCase__			)
		__a           =			bottom_up_cut_rod(lowerCAmelCase__    ,					lowerCAmelCase__			)
		__a           =			naive_cut_rod_recursive(lowerCAmelCase__    ,					lowerCAmelCase__			)

		assert expected_max_revenue == max_rev_top_down
		assert max_rev_top_down == max_rev_bottom_up
		assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
				main()






