






"""simple docstring"""



import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


if TYPE_CHECKING:
						from ... import PreTrainedTokenizerBase, TensorType

__A		:       str  				=		logging.get_logger(__name__)





class 					_UpperCAmelCase       ( _lowerCamelCase							):
					SCREAMING_SNAKE_CASE_		:				Any							    =   "vision-encoder-decoder"
					SCREAMING_SNAKE_CASE_		:				Tuple							    =   True




					def __init__(				self     :						int    ,						**A     :						Dict   )  ->  List[Any]:
							super().__init__(**a_   )
							if "encoder" not in kwargs or "decoder" not in kwargs:
									raise ValueError(
									    F'''A configuraton of type {self.model_type} cannot be instantiated because '''
									    F'''not both `encoder` and `decoder` sub-configurations are passed, but only {kwargs}'''   )

							lowercase_ : Tuple							       =   kwargs.pop('''encoder'''   )
							lowercase_ : Tuple							       =   encoder_config.pop('''model_type'''   )
							lowercase_ : str							       =   kwargs.pop('''decoder'''   )
							lowercase_ : Tuple							       =   decoder_config.pop('''model_type'''   )

							lowercase_ : List[Any]							       =   AutoConfig.for_model(a_    ,						**a_   )
							lowercase_ : Optional[Any]							       =   AutoConfig.for_model(a_    ,						**a_   )
							lowercase_ : Any							       =   True




					@classmethod
					def   A  (				cls     :						Dict    ,						A     :						Union[str, Any]    ,						A     :						str    ,						**A     :						List[str]   )  ->  PretrainedConfig:
							logger.info('''Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''   )
							lowercase_ : List[Any]							       =   True
							lowercase_ : Any							       =   True

							return cls(encoder=encoder_config.to_dict()    ,						decoder=decoder_config.to_dict()    ,						**a_   )






					def   A  (				self     :						List[str]   )  ->  Union[str, Any]:
							lowercase_ : Dict							       =   copy.deepcopy(self.__dict__   )
							lowercase_ : int							       =   self.encoder.to_dict()
							lowercase_ : Union[str, Any]							       =   self.decoder.to_dict()
							lowercase_ : List[str]							       =   self.__class__.model_type
							return output





class 					_UpperCAmelCase       ( _lowerCamelCase							):
					SCREAMING_SNAKE_CASE_		:				Any							    =   version.parse("1.11"							)




					@property
					def   A  (				self     :						Tuple   )  ->  Mapping[str, Mapping[int, str]]:
							return OrderedDict(
							    [
							        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
							    ]   )




					@property
					def   A  (				self     :						List[str]   )  ->  float:
							return 1e-4






					@property
					def   A  (				self     :						Optional[int]   )  ->  Mapping[str, Mapping[int, str]]:
							return OrderedDict({'''last_hidden_state''': {0: '''batch''', 1: '''encoder_sequence'''}}   )





class 					_UpperCAmelCase       ( _lowerCamelCase							):




					@property
					def   A  (				self     :						Dict   )  ->  Mapping[str, Mapping[int, str]]:
							lowercase_ : Any							       =   OrderedDict()
							lowercase_ : List[Any]							       =   {0: """batch""", 1: """past_decoder_sequence + sequence"""}
							lowercase_ : Optional[int]							       =   {0: """batch""", 1: """past_decoder_sequence + sequence"""}
							lowercase_ : Any							       =   {0: """batch""", 1: """encoder_sequence"""}

							return common_inputs






					def   A  (				self     :						int    ,						A     :						Union[str, Any]    ,						A     :						List[str] = -1    ,						A     :						str = -1    ,						A     :						Union[str, Any] = False    ,						A     :						Any = None    ,						)  ->  Mapping[str, Any]:
							import torch

							lowercase_ : Optional[int]							       =   OrderedDict()

							lowercase_ : Union[str, Any]							       =   super().generate_dummy_inputs(
							    a_    ,						batch_size=a_    ,						seq_length=a_    ,						is_pair=a_    ,						framework=a_   )

							lowercase_ : Optional[Any]							       =   dummy_input["""input_ids"""].shape
							lowercase_ : Dict							       =   (batch, encoder_sequence, self._config.encoder_hidden_size)
							lowercase_ : Optional[Any]							       =   dummy_input.pop('''input_ids'''   )
							lowercase_ : Tuple							       =   dummy_input.pop('''attention_mask'''   )
							lowercase_ : Dict							       =   torch.zeros(a_   )

							return common_inputs





class 					_UpperCAmelCase       ( _lowerCamelCase							):




					@property
					def   A  (				self     :						Optional[int]   )  ->  None:
							pass




					def   A  (				self     :						List[Any]    ,						A     :						Optional[Any]   )  ->  OnnxConfig:
							return VisionEncoderDecoderEncoderOnnxConfig(a_   )






					def   A  (				self     :						str    ,						A     :						Tuple    ,						A     :						Union[str, Any]    ,						A     :						List[Any] = "default"   )  ->  OnnxConfig:
							lowercase_ : Optional[int]							       =   encoder_config.hidden_size
							return VisionEncoderDecoderDecoderOnnxConfig(a_    ,						a_   )








'''simple docstring'''






class 							lowercase       :


 """simple docstring"""


 def __init__(							self							)		->   List[str]:
        _UpperCAmelCase  :						int			     = 0
        _UpperCAmelCase  :						Union[str, Any]			     = 0
        _UpperCAmelCase  :						Optional[int]			     = {}







 def _snake_case (							self  ,a_							)		->   Optional[Any]:
        if vertex not in self.adjacency:
               _UpperCAmelCase  :						int			     = {}
               self.num_vertices += 1







 def _snake_case (							self  ,a_  ,a_  ,a_							)		->   int:
        self.add_vertex(a_							)
        self.add_vertex(a_							)

        if head == tail:
               return

        _UpperCAmelCase  :						List[Any]			     = weight
        _UpperCAmelCase  :						Dict			     = weight







 def _snake_case (							self							)		->   Dict:
        _UpperCAmelCase  :						Optional[int]			     = self.get_edges()
        for edge in edges:
               _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						Dict			     = edge
               edges.remove((tail, head, weight)							)
        for i in range(len(a_							)							):
               _UpperCAmelCase  :						str			     = list(edges[i]							)

        edges.sort(key=lambda a_							: e[2]							)
        for i in range(len(a_							) - 1							):
               if edges[i][2] >= edges[i + 1][2]:
                      _UpperCAmelCase  :						Optional[Any]			     = edges[i][2] + 1
        for edge in edges:
               _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						Union[str, Any]			     = edge
               _UpperCAmelCase  :						str			     = weight
               _UpperCAmelCase  :						List[str]			     = weight







 def __str__(							self							)		->   Any:
        _UpperCAmelCase  :						List[Any]			     = """"""
        for tail in self.adjacency:
               for head in self.adjacency[tail]:
                      _UpperCAmelCase  :						List[str]			     = self.adjacency[head][tail]
                      string += f'''{head} -> {tail} == {weight}\n'''
        return string.rstrip("""\n"""							)







 def _snake_case (							self							)		->   str:
        _UpperCAmelCase  :						int			     = []
        for tail in self.adjacency:
               for head in self.adjacency[tail]:
                      output.append((tail, head, self.adjacency[head][tail])							)
        return output







 def _snake_case (							self							)		->   Optional[int]:
        return self.adjacency.keys()







 @staticmethod
 def _snake_case (							a_=None  ,a_=None							)		->   Tuple:
        _UpperCAmelCase  :						List[Any]			     = Graph()
        if vertices is None:
               _UpperCAmelCase  :						List[str]			     = []
        if edges is None:
               _UpperCAmelCase  :						Optional[Any]			     = []
        for vertex in vertices:
               g.add_vertex(a_							)
        for edge in edges:
               g.add_edge(*a_							)
        return g



 class 							lowercase       :


  """simple docstring"""


  def __init__(							self							)		->   int:
         _UpperCAmelCase  :						List[str]			     = {}
         _UpperCAmelCase  :						int			     = {}







  def __len__(							self							)		->   Tuple:
         return len(self.parent							)







  def _snake_case (							self  ,a_							)		->   str:
         if item in self.parent:
                return self.find(a_							)

         _UpperCAmelCase  :						Optional[Any]			     = item
         _UpperCAmelCase  :						List[Any]			     = 0
         return item







  def _snake_case (							self  ,a_							)		->   List[str]:
         if item not in self.parent:
                return self.make_set(a_							)
         if item != self.parent[item]:
                _UpperCAmelCase  :						List[Any]			     = self.find(self.parent[item]							)
         return self.parent[item]







  def _snake_case (							self  ,a_  ,a_							)		->   Union[str, Any]:
         _UpperCAmelCase  :						Any			     = self.find(a_							)
         _UpperCAmelCase  :						List[str]			     = self.find(a_							)

         if roota == roota:
                return roota

         if self.rank[roota] > self.rank[roota]:
                _UpperCAmelCase  :						Any			     = roota
                return roota

         if self.rank[roota] < self.rank[roota]:
                _UpperCAmelCase  :						Any			     = roota
                return roota

         if self.rank[roota] == self.rank[roota]:
                self.rank[roota] += 1
                _UpperCAmelCase  :						List[str]			     = roota
                return roota
         return None







 @staticmethod
 def _snake_case (							a_							)		->   List[Any]:
        _UpperCAmelCase  :						int			     = graph.num_vertices

        _UpperCAmelCase  :						int			     = Graph.UnionFind()
        _UpperCAmelCase  :						Optional[int]			     = []
        while num_components > 1:
               _UpperCAmelCase  :						int			     = {}
               for vertex in graph.get_vertices():
                      _UpperCAmelCase  :						Union[str, Any]			     = -1

               _UpperCAmelCase  :						Tuple			     = graph.get_edges()
               for edge in edges:
                      _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						str			     = edge
                      edges.remove((tail, head, weight)							)
               for edge in edges:
                      _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						Optional[Any]			     = edge
                      _UpperCAmelCase  :						Any			     = union_find.find(a_							)
                      _UpperCAmelCase  :						Any			     = union_find.find(a_							)
                      if seta != seta:
                             if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                                    _UpperCAmelCase  :						Tuple			     = [head, tail, weight]

                             if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                                    _UpperCAmelCase  :						List[str]			     = [head, tail, weight]
               for vertex in cheap_edge:
                      if cheap_edge[vertex] != -1:
                             _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						str			     = cheap_edge[vertex]
                             if union_find.find(a_							) != union_find.find(a_							):
                                    union_find.union(a_  ,a_							)
                                    mst_edges.append(cheap_edge[vertex]							)
                                    _UpperCAmelCase  :						Tuple			     = num_components - 1
        _UpperCAmelCase  :						Optional[int]			     = Graph.build(edges=a_							)
        return mst



