




'''simple docstring'''







import copy
from typing import Dict, Optional

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


A					       =logging.get_logger(__name__)

A					       ={
    '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    (      _lowercase					):
       __a							:	Union[str, Any]  							=   '''oneformer'''
       __a							:	Any  							=   {'''hidden_size''': '''hidden_dim'''}
       def __init__(      self		:      Optional[Any]  ,							lowercase		:      Optional[Dict] = None  ,							lowercase		:      int = 255  ,							lowercase		:      int = 150  ,							lowercase		:      int = 0.1  ,							lowercase		:      float = 2.0  ,							lowercase		:      float = 5.0  ,							lowercase		:      float = 5.0  ,							lowercase		:      float = 0.5  ,							lowercase		:      float = 0.07  ,							lowercase		:      int = 12_544  ,							lowercase		:      float = 3.0  ,							lowercase		:      float = 0.75  ,							lowercase		:      float = 0.02  ,							lowercase		:      float = 1.0  ,							lowercase		:      float = 1E-05  ,							lowercase		:      bool = False  ,							lowercase		:      bool = True  ,							lowercase		:      bool = True  ,							lowercase		:      Optional[list] = [4, 8, 16, 32]  ,							lowercase		:      int = 77  ,							lowercase		:      int = 256  ,							lowercase		:      int = 77  ,							lowercase		:      int = 6  ,							lowercase		:      int = 49_408  ,							lowercase		:      int = 2  ,							lowercase		:      int = 16  ,							lowercase		:      int = 256  ,							lowercase		:      int = 256  ,							lowercase		:      int = 256  ,							lowercase		:      int = 1_024  ,							lowercase		:      str = "GN"  ,							lowercase		:      int = 6  ,							lowercase		:      int = 10  ,							lowercase		:      bool = True  ,							lowercase		:      int = 8  ,							lowercase		:      float = 0.1  ,							lowercase		:      int = 2_048  ,							lowercase		:      bool = False  ,							lowercase		:      bool = False  ,							lowercase		:      int = 2  ,							lowercase		:      int = 4  ,							**lowercase		:      Optional[Any]  ,							):



           '''simple docstring'''

           if backbone_config is None:
               logger.info('''`backbone_config` is unset. Initializing the config with the default `Swin` backbone.'''							)
               UpperCAmelCase     			=						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=_SCREAMING_SNAKE_CASE  ,							out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']  ,							)
           elif isinstance(_SCREAMING_SNAKE_CASE  ,							_SCREAMING_SNAKE_CASE							):
               UpperCAmelCase     			=						backbone_config.get('''model_type'''							)
               UpperCAmelCase     			=						CONFIG_MAPPING[backbone_model_type]
               UpperCAmelCase     			=						config_class.from_dict(_SCREAMING_SNAKE_CASE							)

           UpperCAmelCase     			=						backbone_config

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

           super().__init__(**_SCREAMING_SNAKE_CASE							)







       def        A (      self		:      Optional[Any]							):



           '''simple docstring'''

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








from __future__ import annotations

import sys






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		if n < 0:
				raise ValueError('''Negative arguments are not supported'''			)
		return _fib(_a			)[0]






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		if n == 0:  # (F(0), F(1))
				return (0, 1)

		# F(2n) = F(n)[2F(n+1) − F(n)]
		# F(2n+1) = F(n+1)^2+F(n)^2
		lowerCAmelCase__	,      lowerCAmelCase__  :     Dict       	=   _fib(n // 2			)
		lowerCAmelCase__  :     Dict       	=   a * (b * 2 - a)
		lowerCAmelCase__  :     Union[str, Any]       	=   a * a + b * b
		return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
		lowerCamelCase		=						int(sys.argv[1])
		print(f'''fibonacci({n}) is {fibonacci(n)}''')




