


"""simple docstring"""
import copy
from typing import Dict, List, Optional

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


__SCREAMING_SNAKE_CASE							:    Tuple		=    {
    '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
}

__SCREAMING_SNAKE_CASE							:    str		=    logging.get_logger(__name__)





class      __A     (snake_case__):





							'''simple docstring'''

							__lowercase:		Optional[Any]							      =    """mask2former"""
							__lowercase:		Any							      =    ["""swin"""]
							__lowercase:		Union[str, Any]							      =    {"""hidden_size""": """hidden_dim"""}



							def __init__(				self							:      str		,       UpperCAmelCase_							:      Optional[Dict] = None		,       UpperCAmelCase_							:      int = 256		,       UpperCAmelCase_							:      int = 256		,       UpperCAmelCase_							:      int = 256		,       UpperCAmelCase_							:      int = 1_024		,       UpperCAmelCase_							:      str = "relu"		,       UpperCAmelCase_							:      int = 6		,       UpperCAmelCase_							:      int = 10		,       UpperCAmelCase_							:      int = 8		,       UpperCAmelCase_							:      float = 0.0		,       UpperCAmelCase_							:      int = 2_048		,       UpperCAmelCase_							:      bool = False		,       UpperCAmelCase_							:      bool = False		,       UpperCAmelCase_							:      int = 4		,       UpperCAmelCase_							:      int = 255		,       UpperCAmelCase_							:      int = 100		,       UpperCAmelCase_							:      float = 0.1		,       UpperCAmelCase_							:      float = 2.0		,       UpperCAmelCase_							:      float = 5.0		,       UpperCAmelCase_							:      float = 5.0		,       UpperCAmelCase_							:      int = 12_544		,       UpperCAmelCase_							:      float = 3.0		,       UpperCAmelCase_							:      float = 0.75		,       UpperCAmelCase_							:      float = 0.02		,       UpperCAmelCase_							:      float = 1.0		,       UpperCAmelCase_							:      bool = True		,       UpperCAmelCase_							:      List[int] = [4, 8, 16, 32]		,       UpperCAmelCase_							:      bool = None		,       **UpperCAmelCase_							:      Optional[Any]		,       )					->Dict:



														"""simple docstring"""



														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=UpperCAmelCase_		,       out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]		,       )

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

														# 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__(**UpperCAmelCase_       )



							@classmethod
							def 		lowerCAmelCase       (				cls							:      Tuple		,       UpperCAmelCase_							:      PretrainedConfig		,       **UpperCAmelCase_							:      List[Any]       )					->int:



														"""simple docstring"""



														return cls(
														    backbone_config=UpperCAmelCase_		,       **UpperCAmelCase_		,       )



							def 		lowerCAmelCase       (				self							:      int       )					->Dict[str, any]:



														"""simple docstring"""



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







"""simple docstring"""
def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				list:

							# bit count represents no. of bits in the gray code
							if bit_count < 0:
														raise ValueError("""The given input must be positive"""				)

							# get the generated string sequence
							snake_case_           =		gray_code_sequence_string(_SCREAMING_SNAKE_CASE				)
							#
							# convert them to integers
							for i in range(len(_SCREAMING_SNAKE_CASE				)				):
														snake_case_           =		int(sequence[i]				, 2				)

							return sequence







def 						_a				(      _SCREAMING_SNAKE_CASE				)    ->				list:

							# The approach is a recursive one
							# Base case achieved when either n = 0 or n=1
							if bit_count == 0:
														return ["0"]

							if bit_count == 1:
														return ["0", "1"]

							snake_case_           =		1 << bit_count  # defines the length of the sequence
							# 1<< n is equivalent to 2^n

							# recursive answer will generate answer for n-1 bits
							snake_case_           =		gray_code_sequence_string(bit_count - 1				)

							snake_case_           =		[]

							# append 0 to first half of the smaller sequence generated
							for i in range(seq_len // 2				):
														snake_case_           =		"""0""" + smaller_sequence[i]
														sequence.append(_SCREAMING_SNAKE_CASE				)

							# append 1 to second half ... start from the end of the list
							for i in reversed(range(seq_len // 2				)				):
														snake_case_           =		"""1""" + smaller_sequence[i]
														sequence.append(_SCREAMING_SNAKE_CASE				)

							return sequence


if __name__ == "__main__":
				import doctest

				doctest.testmod()



