




'''simple docstring'''







# Imports
import numpy as np







class 					_a :





     '''simple docstring'''



     def __init__(				self							,__a=None							,__a=None							,__a=None							,__a=None							,__a=None							)      ->				str:
          self.set_matricies(red=__a							,green=__a							,blue=__a							,red_edge=__a							,nir=__a							)







     def 			snake_case_      (				self							,__a=None							,__a=None							,__a=None							,__a=None							,__a=None							)      ->				List[Any]:
          if red is not None:
               snake_case			:      int        =			red
          if green is not None:
               snake_case			:      List[str]        =			green
          if blue is not None:
               snake_case			:      Dict        =			blue
          if red_edge is not None:
               snake_case			:      str        =			red_edge
          if nir is not None:
               snake_case			:      Dict        =			nir
          return True







     def 			snake_case_      (				self							,__a=""							,__a=None							,__a=None							,__a=None							,__a=None							,__a=None							)      ->				int:
          self.set_matricies(red=__a							,green=__a							,blue=__a							,red_edge=__a							,nir=__a							)
          snake_case			:      List[Any]        =			{
              """ARVI2""": self.arvaa,
              """CCCI""": self.ccci,
              """CVI""": self.cvi,
              """GLI""": self.gli,
              """NDVI""": self.ndvi,
              """BNDVI""": self.bndvi,
              """redEdgeNDVI""": self.red_edge_ndvi,
              """GNDVI""": self.gndvi,
              """GBNDVI""": self.gbndvi,
              """GRNDVI""": self.grndvi,
              """RBNDVI""": self.rbndvi,
              """PNDVI""": self.pndvi,
              """ATSAVI""": self.atsavi,
              """BWDRVI""": self.bwdrvi,
              """CIgreen""": self.ci_green,
              """CIrededge""": self.ci_rededge,
              """CI""": self.ci,
              """CTVI""": self.ctvi,
              """GDVI""": self.gdvi,
              """EVI""": self.evi,
              """GEMI""": self.gemi,
              """GOSAVI""": self.gosavi,
              """GSAVI""": self.gsavi,
              """Hue""": self.hue,
              """IVI""": self.ivi,
              """IPVI""": self.ipvi,
              """I""": self.i,
              """RVI""": self.rvi,
              """MRVI""": self.mrvi,
              """MSAVI""": self.m_savi,
              """NormG""": self.norm_g,
              """NormNIR""": self.norm_nir,
              """NormR""": self.norm_r,
              """NGRDI""": self.ngrdi,
              """RI""": self.ri,
              """S""": self.s,
              """IF""": self._if,
              """DVI""": self.dvi,
              """TVI""": self.tvi,
              """NDRE""": self.ndre,
          }

          try:
               return funcs[index]()
          except KeyError:
               print("""Index not in the list!"""							)
               return False







     def 			snake_case_      (				self							)      ->				Optional[int]:
          return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))







     def 			snake_case_      (				self							)      ->				List[Any]:
          return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
              (self.nir - self.red) / (self.nir + self.red)
          )







     def 			snake_case_      (				self							)      ->				Tuple:
          return self.nir * (self.red / (self.green**2))







     def 			snake_case_      (				self							)      ->				List[str]:
          return (2 * self.green - self.red - self.blue) / (
              2 * self.green + self.red + self.blue
          )







     def 			snake_case_      (				self							)      ->				List[Any]:
          return (self.nir - self.red) / (self.nir + self.red)







     def 			snake_case_      (				self							)      ->				int:
          return (self.nir - self.blue) / (self.nir + self.blue)







     def 			snake_case_      (				self							)      ->				Any:
          return (self.redEdge - self.red) / (self.redEdge + self.red)







     def 			snake_case_      (				self							)      ->				Tuple:
          return (self.nir - self.green) / (self.nir + self.green)







     def 			snake_case_      (				self							)      ->				Union[str, Any]:
          return (self.nir - (self.green + self.blue)) / (
              self.nir + (self.green + self.blue)
          )







     def 			snake_case_      (				self							)      ->				List[Any]:
          return (self.nir - (self.green + self.red)) / (
              self.nir + (self.green + self.red)
          )







     def 			snake_case_      (				self							)      ->				List[str]:
          return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          return (self.nir - (self.green + self.red + self.blue)) / (
              self.nir + (self.green + self.red + self.blue)
          )







     def 			snake_case_      (				self							,__a=0.08							,__a=1.22							,__a=0.03							)      ->				Dict:
          return a * (
              (self.nir - a * self.red - b)
              / (a * self.nir + self.red - a * b + x * (1 + a**2))
          )







     def 			snake_case_      (				self							)      ->				List[str]:
          return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          return (self.nir / self.green) - 1







     def 			snake_case_      (				self							)      ->				Any:
          return (self.nir / self.redEdge) - 1







     def 			snake_case_      (				self							)      ->				List[Any]:
          return (self.red - self.blue) / self.red







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          snake_case			:      Dict        =			self.ndvi()
          return ((ndvi + 0.5) / (abs(ndvi + 0.5							))) * (abs(ndvi + 0.5							) ** (1 / 2))







     def 			snake_case_      (				self							)      ->				List[str]:
          return self.nir - self.green







     def 			snake_case_      (				self							)      ->				int:
          return 2.5 * (
              (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
          )







     def 			snake_case_      (				self							)      ->				Any:
          snake_case			:      Union[str, Any]        =			(2 * (self.nir**2 - self.red**2) + 1.5 * self.nir + 0.5 * self.red) / (
              self.nir + self.red + 0.5
          )
          return n * (1 - 0.25 * n) - (self.red - 0.125) / (1 - self.red)







     def 			snake_case_      (				self							,__a=0.16							)      ->				List[str]:
          return (self.nir - self.green) / (self.nir + self.green + y)







     def 			snake_case_      (				self							,__a=0.5							)      ->				Any:
          return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)







     def 			snake_case_      (				self							)      ->				Dict:
          return np.arctan(
              ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)							)







     def 			snake_case_      (				self							,__a=None							,__a=None							)      ->				Dict:
          return (self.nir - b) / (a * self.red)







     def 			snake_case_      (				self							)      ->				Optional[int]:
          return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)







     def 			snake_case_      (				self							)      ->				List[Any]:
          return (self.red + self.green + self.blue) / 30.5







     def 			snake_case_      (				self							)      ->				Tuple:
          return self.nir / self.red







     def 			snake_case_      (				self							)      ->				Union[str, Any]:
          return (self.rvi() - 1) / (self.rvi() + 1)







     def 			snake_case_      (				self							)      ->				List[str]:
          return (
              (2 * self.nir + 1)
              - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
          ) / 2







     def 			snake_case_      (				self							)      ->				List[str]:
          return self.green / (self.nir + self.red + self.green)







     def 			snake_case_      (				self							)      ->				Dict:
          return self.nir / (self.nir + self.red + self.green)







     def 			snake_case_      (				self							)      ->				Dict:
          return self.red / (self.nir + self.red + self.green)







     def 			snake_case_      (				self							)      ->				Union[str, Any]:
          return (self.green - self.red) / (self.green + self.red)







     def 			snake_case_      (				self							)      ->				List[str]:
          return (self.red - self.green) / (self.red + self.green)







     def 			snake_case_      (				self							)      ->				Tuple:
          snake_case			:      List[str]        =			np.max([np.max(self.red							), np.max(self.green							), np.max(self.blue							)]							)
          snake_case			:      Optional[Any]        =			np.min([np.min(self.red							), np.min(self.green							), np.min(self.blue							)]							)
          return (max_value - min_value) / max_value







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          return (2 * self.red - self.green - self.blue) / (self.green - self.blue)







     def 			snake_case_      (				self							)      ->				Optional[int]:
          return self.nir / self.red







     def 			snake_case_      (				self							)      ->				int:
          return (self.ndvi() + 0.5) ** (1 / 2)







     def 			snake_case_      (				self							)      ->				Tuple:
          return (self.nir - self.redEdge) / (self.nir + self.redEdge)









'''simple docstring'''







import copy

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


lowercase      :   Tuple      =       logging.get_logger(__name__)

lowercase      :   Dict      =       {
    """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}







class 					_a (a__	):





     '''simple docstring'''



     lowerCAmelCase_  :     str          =					"""deta"""
     lowerCAmelCase_  :     Any          =					{
         """hidden_size""": """d_model""",
         """num_attention_heads""": """encoder_attention_heads""",
     }







     def __init__(				self							,__a=None							,__a=900							,__a=2_048							,__a=6							,__a=2_048							,__a=8							,__a=6							,__a=1_024							,__a=8							,__a=0.0							,__a=True							,__a="relu"							,__a=256							,__a=0.1							,__a=0.0							,__a=0.0							,__a=0.02							,__a=1.0							,__a=True							,__a=False							,__a="sine"							,__a=5							,__a=4							,__a=4							,__a=True							,__a=300							,__a=True							,__a=True							,__a=1							,__a=5							,__a=2							,__a=1							,__a=1							,__a=5							,__a=2							,__a=0.1							,__a=0.25							,**__a							,)      ->				int:
          if backbone_config is None:
               logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""							)
               snake_case			:      int        =			CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]							)
          else:
               if isinstance(__a							,__a							):
                    snake_case			:      str        =			backbone_config.pop("""model_type"""							)
                    snake_case			:      Optional[Any]        =			CONFIG_MAPPING[backbone_model_type]
                    snake_case			:      List[Any]        =			config_class.from_dict(__a							)

          snake_case			:      Any        =			backbone_config
          snake_case			:      Optional[Any]        =			num_queries
          snake_case			:      Dict        =			max_position_embeddings
          snake_case			:      int        =			d_model
          snake_case			:      str        =			encoder_ffn_dim
          snake_case			:      Dict        =			encoder_layers
          snake_case			:      List[Any]        =			encoder_attention_heads
          snake_case			:      int        =			decoder_ffn_dim
          snake_case			:      List[Any]        =			decoder_layers
          snake_case			:      Dict        =			decoder_attention_heads
          snake_case			:      Dict        =			dropout
          snake_case			:      Dict        =			attention_dropout
          snake_case			:      List[Any]        =			activation_dropout
          snake_case			:      Dict        =			activation_function
          snake_case			:      List[Any]        =			init_std
          snake_case			:      Any        =			init_xavier_std
          snake_case			:      List[Any]        =			encoder_layerdrop
          snake_case			:      Optional[Any]        =			auxiliary_loss
          snake_case			:      Optional[int]        =			position_embedding_type
          # deformable attributes
          snake_case			:      Tuple        =			num_feature_levels
          snake_case			:      List[Any]        =			encoder_n_points
          snake_case			:      Dict        =			decoder_n_points
          snake_case			:      int        =			two_stage
          snake_case			:      Any        =			two_stage_num_proposals
          snake_case			:      List[str]        =			with_box_refine
          snake_case			:      Tuple        =			assign_first_stage
          if two_stage is True and with_box_refine is False:
               raise ValueError("""If two_stage is True, with_box_refine must be True."""							)
          # Hungarian matcher
          snake_case			:      Optional[int]        =			class_cost
          snake_case			:      int        =			bbox_cost
          snake_case			:      Optional[int]        =			giou_cost
          # Loss coefficients
          snake_case			:      str        =			mask_loss_coefficient
          snake_case			:      Any        =			dice_loss_coefficient
          snake_case			:      List[Any]        =			bbox_loss_coefficient
          snake_case			:      List[Any]        =			giou_loss_coefficient
          snake_case			:      List[str]        =			eos_coefficient
          snake_case			:      Optional[Any]        =			focal_alpha
          super().__init__(is_encoder_decoder=__a							,**__a							)







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.encoder_attention_heads







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.d_model







     def 			snake_case_      (				self							)      ->				List[str]:
          snake_case			:      List[str]        =			copy.deepcopy(self.__dict__							)
          snake_case			:      List[str]        =			self.backbone_config.to_dict()
          snake_case			:      List[Any]        =			self.__class__.model_type
          return output



