import copy
from typing import Dict, Optional

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


lowerCAmelCase__  	=      logging.get_logger(__name__)

lowerCAmelCase__  	=      {
    "shi-labs/oneformer_ade20k_swin_tiny": (
        "https://huggingface.co/shi-labs/oneformer_ade20k_swin_tiny/blob/main/config.json"
    ),
    # See all OneFormer models at https://huggingface.co/models?filter=oneformer
}
class 	_a  (							lowerCamelCase_					):



	"""simple docstring"""



	__SCREAMING_SNAKE_CASE              =					'oneformer'
	__SCREAMING_SNAKE_CASE              =					{'hidden_size': 'hidden_dim'}


	def __init__(   self       ,  lowerCAmelCase_ = None       ,  lowerCAmelCase_ = 255       ,  lowerCAmelCase_ = 150       ,  lowerCAmelCase_ = 0.1       ,  lowerCAmelCase_ = 2.0       ,  lowerCAmelCase_ = 5.0       ,  lowerCAmelCase_ = 5.0       ,  lowerCAmelCase_ = 0.5       ,  lowerCAmelCase_ = 0.0_7       ,  lowerCAmelCase_ = 12544       ,  lowerCAmelCase_ = 3.0       ,  lowerCAmelCase_ = 0.7_5       ,  lowerCAmelCase_ = 0.0_2       ,  lowerCAmelCase_ = 1.0       ,  lowerCAmelCase_ = 1e-05       ,  lowerCAmelCase_ = False       ,  lowerCAmelCase_ = True       ,  lowerCAmelCase_ = True       ,  lowerCAmelCase_ = [4, 8, 16, 32]       ,  lowerCAmelCase_ = 77       ,  lowerCAmelCase_ = 256       ,  lowerCAmelCase_ = 77       ,  lowerCAmelCase_ = 6       ,  lowerCAmelCase_ = 49408       ,  lowerCAmelCase_ = 2       ,  lowerCAmelCase_ = 16       ,  lowerCAmelCase_ = 256       ,  lowerCAmelCase_ = 256       ,  lowerCAmelCase_ = 256       ,  lowerCAmelCase_ = 1024       ,  lowerCAmelCase_ = "GN"       ,  lowerCAmelCase_ = 6       ,  lowerCAmelCase_ = 10       ,  lowerCAmelCase_ = True       ,  lowerCAmelCase_ = 8       ,  lowerCAmelCase_ = 0.1       ,  lowerCAmelCase_ = 2048       ,  lowerCAmelCase_ = False       ,  lowerCAmelCase_ = False       ,  lowerCAmelCase_ = 2       ,  lowerCAmelCase_ = 4       ,  **lowerCAmelCase_       ,  ):
		if backbone_config is None:
			logger.info("`backbone_config` is unset. Initializing the config with the default `Swin` backbone."       )
			_lowercase   =CONFIG_MAPPING["swin"](
			    image_size=224       ,  in_channels=3       ,  patch_size=4       ,  embed_dim=96       ,  depths=[2, 2, 6, 2]       ,  num_heads=[3, 6, 12, 24]       ,  window_size=7       ,  drop_path_rate=0.3       ,  use_absolute_embeddings=lowerCAmelCase_       ,  out_features=["stage1", "stage2", "stage3", "stage4"]       ,  )
		elif isinstance(lowerCAmelCase_       ,  lowerCAmelCase_       ):
			_lowercase   =backbone_config.get("model_type"       )
			_lowercase   =CONFIG_MAPPING[backbone_model_type]
			_lowercase   =config_class.from_dict(lowerCAmelCase_       )

		_lowercase   =backbone_config

		_lowercase   =ignore_value
		_lowercase   =num_queries
		_lowercase   =no_object_weight
		_lowercase   =class_weight
		_lowercase   =mask_weight
		_lowercase   =dice_weight
		_lowercase   =contrastive_weight
		_lowercase   =contrastive_temperature
		_lowercase   =train_num_points
		_lowercase   =oversample_ratio
		_lowercase   =importance_sample_ratio
		_lowercase   =init_std
		_lowercase   =init_xavier_std
		_lowercase   =layer_norm_eps
		_lowercase   =is_training
		_lowercase   =use_auxiliary_loss
		_lowercase   =output_auxiliary_logits
		_lowercase   =strides
		_lowercase   =task_seq_len
		_lowercase   =text_encoder_width
		_lowercase   =text_encoder_context_length
		_lowercase   =text_encoder_num_layers
		_lowercase   =text_encoder_vocab_size
		_lowercase   =text_encoder_proj_layers
		_lowercase   =text_encoder_n_ctx
		_lowercase   =conv_dim
		_lowercase   =mask_dim
		_lowercase   =hidden_dim
		_lowercase   =encoder_feedforward_dim
		_lowercase   =norm
		_lowercase   =encoder_layers
		_lowercase   =decoder_layers
		_lowercase   =use_task_norm
		_lowercase   =num_attention_heads
		_lowercase   =dropout
		_lowercase   =dim_feedforward
		_lowercase   =pre_norm
		_lowercase   =enforce_input_proj
		_lowercase   =query_dec_layers
		_lowercase   =common_stride
		_lowercase   =decoder_layers

		super().__init__(**lowerCAmelCase_       )


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





def 	__lowerCamelCase							(				)      ->       Dict:
	_lowercase   =1

	while True:
		if (
		    sorted(str(__a		)		)
		    == sorted(str(2 * i		)		)
		    == sorted(str(3 * i		)		)
		    == sorted(str(4 * i		)		)
		    == sorted(str(5 * i		)		)
		    == sorted(str(6 * i		)		)
		):
			return i

		i += 1


if __name__ == "__main__":
						print(solution())




