
"""simple docstring"""





# Imports
import numpy as np


class A_	:




  '''simple docstring'''







  def __init__(		self				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None  ):

     """simple docstring"""
     self.set_matricies(red=lowercase_				,   green=lowercase_				,   blue=lowercase_				,   red_edge=lowercase_				,   nir=lowercase_  )







  def        UpperCamelCase__					(		self				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None  ):

     """simple docstring"""
     if red is not None:
        UpperCAmelCase_					:					Union[str, Any]			     =    red
     if green is not None:
        UpperCAmelCase_					:					Dict			     =    green
     if blue is not None:
        UpperCAmelCase_					:					Optional[int]			     =    blue
     if red_edge is not None:
        UpperCAmelCase_					:					Optional[int]			     =    red_edge
     if nir is not None:
        UpperCAmelCase_					:					str			     =    nir
     return True







  def        UpperCamelCase__					(		self				,   lowercase_=""				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None				,   lowercase_=None  ):

     """simple docstring"""
     self.set_matricies(red=lowercase_				,   green=lowercase_				,   blue=lowercase_				,   red_edge=lowercase_				,   nir=lowercase_  )
     UpperCAmelCase_					:					str			     =    {
         "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        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return -0.18 + (1.17 * ((self.nir - self.red) / (self.nir + self.red)))







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
         (self.nir - self.red) / (self.nir + self.red)
     )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.nir * (self.red / (self.green**2))







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (2 * self.green - self.red - self.blue) / (
         2 * self.green + self.red + self.blue
     )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - self.red) / (self.nir + self.red)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - self.blue) / (self.nir + self.blue)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.redEdge - self.red) / (self.redEdge + self.red)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - self.green) / (self.nir + self.green)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - (self.green + self.blue)) / (
         self.nir + (self.green + self.blue)
     )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - (self.green + self.red)) / (
         self.nir + (self.green + self.red)
     )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - (self.green + self.red + self.blue)) / (
         self.nir + (self.green + self.red + self.blue)
     )







  def        UpperCamelCase__					(		self				,   lowercase_=0.08				,   lowercase_=1.22				,   lowercase_=0.03  ):

     """simple docstring"""
     return a * (
         (self.nir - a * self.red - b)
         / (a * self.nir + self.red - a * b + x * (1 + a**2))
     )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir / self.green) - 1







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir / self.redEdge) - 1







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.red - self.blue) / self.red







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    self.ndvi()
     return ((ndvi + 0.5) / (abs(ndvi + 0.5  ))) * (abs(ndvi + 0.5  ) ** (1 / 2))







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.nir - self.green







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return 2.5 * (
         (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
     )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    (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 - 0.1_25) / (1 - self.red)







  def        UpperCamelCase__					(		self				,   lowercase_=0.16  ):

     """simple docstring"""
     return (self.nir - self.green) / (self.nir + self.green + y)







  def        UpperCamelCase__					(		self				,   lowercase_=0.5  ):

     """simple docstring"""
     return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return np.arctan(
         ((2 * self.red - self.green - self.blue) / 30.5) * (self.green - self.blue)  )







  def        UpperCamelCase__					(		self				,   lowercase_=None				,   lowercase_=None  ):

     """simple docstring"""
     return (self.nir - b) / (a * self.red)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.red + self.green + self.blue) / 30.5







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.nir / self.red







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.rvi() - 1) / (self.rvi() + 1)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (
         (2 * self.nir + 1)
         - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
     ) / 2







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.green / (self.nir + self.red + self.green)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.nir / (self.nir + self.red + self.green)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.red / (self.nir + self.red + self.green)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.green - self.red) / (self.green + self.red)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.red - self.green) / (self.red + self.green)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					str			     =    np.max([np.max(self.red  ), np.max(self.green  ), np.max(self.blue  )]  )
     UpperCAmelCase_					:					Optional[Any]			     =    np.min([np.min(self.red  ), np.min(self.green  ), np.min(self.blue  )]  )
     return (max_value - min_value) / max_value







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (2 * self.red - self.green - self.blue) / (self.green - self.blue)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return self.nir / self.red







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.ndvi() + 0.5) ** (1 / 2)







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     return (self.nir - self.redEdge) / (self.nir + self.redEdge)






import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING


_A		       =						logging.get_logger(__name__)

_A		       =						{
    'Salesforce/instruct-blip-flan-t5': 'https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json',
}






class     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Optional[int]      =  "instructblip_vision_model"






    def __init__(			self					,   A_=1408					,   A_=6144					,   A_=39					,   A_=16					,   A_=224					,   A_=14					,   A_="gelu"					,   A_=1E-6					,   A_=0.0					,   A_=1E-10					,   A_=True					,   **A_					,   )  ->       Tuple:
         super().__init__(**A_    )

         __UpperCamelCase    							=hidden_size
         __UpperCamelCase    							=intermediate_size
         __UpperCamelCase    							=num_hidden_layers
         __UpperCamelCase    							=num_attention_heads
         __UpperCamelCase    							=patch_size
         __UpperCamelCase    							=image_size
         __UpperCamelCase    							=initializer_range
         __UpperCamelCase    							=attention_dropout
         __UpperCamelCase    							=layer_norm_eps
         __UpperCamelCase    							=hidden_act
         __UpperCamelCase    							=qkv_bias






    @classmethod
    def _a					(			cls					,   A_					,   **A_    )  ->       "PretrainedConfig":
         cls._set_token_in_kwargs(A_    )

         __UpperCamelCase							,      __UpperCamelCase    							=cls.get_config_dict(A_					,   **A_    )

         # get the vision config dict if we are loading from InstructBlipConfig
         if config_dict.get('model_type'    ) == "instructblip":
              __UpperCamelCase    							=config_dict['vision_config']

         if "model_type" in config_dict and hasattr(cls					,   'model_type'    ) and config_dict["model_type"] != cls.model_type:
              logger.warning(
                  f'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
                  f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'    )

         return cls.from_dict(A_					,   **A_    )






class     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Optional[Any]      =  "instructblip_qformer"






    def __init__(			self					,   A_=30522					,   A_=768					,   A_=12					,   A_=12					,   A_=3072					,   A_="gelu"					,   A_=0.1					,   A_=0.1					,   A_=512					,   A_=0.02					,   A_=1E-12					,   A_=0					,   A_="absolute"					,   A_=2					,   A_=1408					,   **A_					,   )  ->       Optional[Any]:
         super().__init__(pad_token_id=A_					,   **A_    )

         __UpperCamelCase    							=vocab_size
         __UpperCamelCase    							=hidden_size
         __UpperCamelCase    							=num_hidden_layers
         __UpperCamelCase    							=num_attention_heads
         __UpperCamelCase    							=hidden_act
         __UpperCamelCase    							=intermediate_size
         __UpperCamelCase    							=hidden_dropout_prob
         __UpperCamelCase    							=attention_probs_dropout_prob
         __UpperCamelCase    							=max_position_embeddings
         __UpperCamelCase    							=initializer_range
         __UpperCamelCase    							=layer_norm_eps
         __UpperCamelCase    							=position_embedding_type
         __UpperCamelCase    							=cross_attention_frequency
         __UpperCamelCase    							=encoder_hidden_size






    @classmethod
    def _a					(			cls					,   A_					,   **A_    )  ->       "PretrainedConfig":
         cls._set_token_in_kwargs(A_    )

         __UpperCamelCase							,      __UpperCamelCase    							=cls.get_config_dict(A_					,   **A_    )

         # get the qformer config dict if we are loading from InstructBlipConfig
         if config_dict.get('model_type'    ) == "instructblip":
              __UpperCamelCase    							=config_dict['qformer_config']

         if "model_type" in config_dict and hasattr(cls					,   'model_type'    ) and config_dict["model_type"] != cls.model_type:
              logger.warning(
                  f'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
                  f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'    )

         return cls.from_dict(A_					,   **A_    )






class     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Optional[int]      =  "instructblip"
    UpperCAmelCase__						:		Optional[Any]      =  True






    def __init__(			self					,   A_=None					,   A_=None					,   A_=None					,   A_=32					,   **A_    )  ->       List[str]:
         super().__init__(**A_    )

         if vision_config is None:
              __UpperCamelCase    							={}
              logger.info('vision_config is None. initializing the InstructBlipVisionConfig with default values.'    )

         if qformer_config is None:
              __UpperCamelCase    							={}
              logger.info('qformer_config is None. Initializing the InstructBlipQFormerConfig with default values.'    )

         if text_config is None:
              __UpperCamelCase    							={}
              logger.info('text_config is None. Initializing the text config with default values (`OPTConfig`).'    )

         __UpperCamelCase    							=InstructBlipVisionConfig(**A_    )
         __UpperCamelCase    							=InstructBlipQFormerConfig(**A_    )
         __UpperCamelCase    							=text_config['model_type'] if 'model_type' in text_config else 'opt'
         __UpperCamelCase    							=CONFIG_MAPPING[text_model_type](**A_    )

         __UpperCamelCase    							=self.text_config.tie_word_embeddings
         __UpperCamelCase    							=self.text_config.is_encoder_decoder

         __UpperCamelCase    							=num_query_tokens
         __UpperCamelCase    							=self.vision_config.hidden_size
         __UpperCamelCase    							=self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
         __UpperCamelCase    							=1.0
         __UpperCamelCase    							=0.02






    @classmethod
    def _a					(			cls					,   A_					,   A_					,   A_					,   **A_					,   )  ->       Optional[Any]:
         return cls(
             vision_config=vision_config.to_dict()					,   qformer_config=qformer_config.to_dict()					,   text_config=text_config.to_dict()					,   **A_					,   )






    def _a					(			self    )  ->       Optional[Any]:
         __UpperCamelCase    							=copy.deepcopy(self.__dict__    )
         __UpperCamelCase    							=self.vision_config.to_dict()
         __UpperCamelCase    							=self.qformer_config.to_dict()
         __UpperCamelCase    							=self.text_config.to_dict()
         __UpperCamelCase    							=self.__class__.model_type
         return output





