






from __future__ import annotations

from typing import Any


class    __lowercase   :







     '''simple docstring'''




     def __init__(					self							:      str			,						UpperCamelCase_							:      int					):


         """simple docstring"""



         __A       =						num_of_nodes
         __A       =						[]
         __A       =						{}




     def 		lowerCAmelCase_  (					self							:      Optional[Any]			,						UpperCamelCase_							:      int			,						UpperCamelCase_							:      int			,						UpperCamelCase_							:      int					):


         """simple docstring"""



         self.m_edges.append([u_node, v_node, weight]					)




     def 		lowerCAmelCase_  (					self							:      int			,						UpperCamelCase_							:      int					):


         """simple docstring"""



         if self.m_component[u_node] == u_node:
             return u_node
         return self.find_component(self.m_component[u_node]					)




     def 		lowerCAmelCase_  (					self							:      Any			,						UpperCamelCase_							:      int					):


         """simple docstring"""



         if self.m_component[u_node] != u_node:
             for k in self.m_component:
                 __A       =						self.find_component(UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      Dict			,						UpperCamelCase_							:      list[int]			,						UpperCamelCase_							:      int			,						UpperCamelCase_							:      int					):


         """simple docstring"""



         if component_size[u_node] <= component_size[v_node]:
             __A       =						v_node
             component_size[v_node] += component_size[u_node]
             self.set_component(UpperCamelCase_					)

         elif component_size[u_node] >= component_size[v_node]:
             __A       =						self.find_component(UpperCamelCase_					)
             component_size[u_node] += component_size[v_node]
             self.set_component(UpperCamelCase_					)





     def 		lowerCAmelCase_  (					self							:      Optional[Any]					):


         """simple docstring"""



         __A       =						[]
         __A       =						0

         __A       =						[-1] * self.m_num_of_nodes

         # A list of components (initialized to all of the nodes)
         for node in range(self.m_num_of_nodes					):
             self.m_component.update({node: node}					)
             component_size.append(1					)

         __A       =						self.m_num_of_nodes

         while num_of_components > 1:
             for edge in self.m_edges:
                 __A     ,						__A     ,						__A       =						edge

                 __A       =						self.m_component[u]
                 __A       =						self.m_component[v]

                 if u_component != v_component:

                     for component in (u_component, v_component):
                         if (
                             minimum_weight_edge[component] == -1
                             or minimum_weight_edge[component][2] > w
                         ):
                             __A       =						[u, v, w]

             for edge in minimum_weight_edge:
                 if isinstance(UpperCamelCase_			,						UpperCamelCase_					):
                     __A     ,						__A     ,						__A       =						edge

                     __A       =						self.m_component[u]
                     __A       =						self.m_component[v]

                     if u_component != v_component:
                         mst_weight += w
                         self.union(UpperCamelCase_			,						UpperCamelCase_			,						UpperCamelCase_					)
                         print(F"Added edge [{u} - {v}]\nAdded weight: {w}\n"					)
                         num_of_components -= 1

             __A       =						[-1] * self.m_num_of_nodes
         print(F"The total weight of the minimal spanning tree is: {mst_weight}"					)



def       _SCREAMING_SNAKE_CASE    (			)    ->   None:





    """simple docstring"""



if __name__ == "__main__":
  import doctest

  doctest.testmod()












from ...configuration_utils import PretrainedConfig
from ...utils import logging


__a   :							Optional[Any]						= logging.get_logger(__name__)

__a   :							Dict						= {
    "google/realm-cc-news-pretrained-embedder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-encoder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-scorer": (
        "https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-openqa": (
        "https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"
    ),
    "google/realm-orqa-nq-openqa": "https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json",
    "google/realm-orqa-nq-reader": "https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json",
    "google/realm-orqa-wq-openqa": "https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json",
    "google/realm-orqa-wq-reader": "https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json",
    # See all REALM models at https://huggingface.co/models?filter=realm
}


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					"realm"




     def __init__(					self							:      str			,						UpperCamelCase_							:      List[Any]=30_522			,						UpperCamelCase_							:      Dict=768			,						UpperCamelCase_							:      Union[str, Any]=128			,						UpperCamelCase_							:      Tuple=12			,						UpperCamelCase_							:      Optional[Any]=12			,						UpperCamelCase_							:      Optional[int]=8			,						UpperCamelCase_							:      str=3_072			,						UpperCamelCase_							:      List[str]="gelu_new"			,						UpperCamelCase_							:      Optional[int]=0.1			,						UpperCamelCase_							:      Optional[int]=0.1			,						UpperCamelCase_							:      str=512			,						UpperCamelCase_							:      int=2			,						UpperCamelCase_							:      str=0.02			,						UpperCamelCase_							:      List[Any]=1e-12			,						UpperCamelCase_							:      str=256			,						UpperCamelCase_							:      List[str]=10			,						UpperCamelCase_							:      int=1e-3			,						UpperCamelCase_							:      List[str]=5			,						UpperCamelCase_							:      Tuple=320			,						UpperCamelCase_							:      List[str]=13_353_718			,						UpperCamelCase_							:      Tuple=5_000			,						UpperCamelCase_							:      Optional[int]=1			,						UpperCamelCase_							:      List[str]=0			,						UpperCamelCase_							:      Union[str, Any]=2			,						**UpperCamelCase_							:      List[Any]			,						):


         """simple docstring"""



         super().__init__(pad_token_id=UpperCamelCase_			,						bos_token_id=UpperCamelCase_			,						eos_token_id=UpperCamelCase_			,						**UpperCamelCase_					)

         # Common config
         __A       =						vocab_size
         __A       =						max_position_embeddings
         __A       =						hidden_size
         __A       =						retriever_proj_size
         __A       =						num_hidden_layers
         __A       =						num_attention_heads
         __A       =						num_candidates
         __A       =						intermediate_size
         __A       =						hidden_act
         __A       =						hidden_dropout_prob
         __A       =						attention_probs_dropout_prob
         __A       =						initializer_range
         __A       =						type_vocab_size
         __A       =						layer_norm_eps

         # Reader config
         __A       =						span_hidden_size
         __A       =						max_span_width
         __A       =						reader_layer_norm_eps
         __A       =						reader_beam_size
         __A       =						reader_seq_len

         # Retrieval config
         __A       =						num_block_records
         __A       =						searcher_beam_size




