






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__a   :							Tuple						= logging.get_logger(__name__)

__a   :							int						= {
    "facebook/data2vec-text-base": "https://huggingface.co/data2vec/resolve/main/config.json",
}


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					"data2vec-text"




     def __init__(					self							:      Optional[Any]			,						UpperCamelCase_							:      List[Any]=30_522			,						UpperCamelCase_							:      List[Any]=768			,						UpperCamelCase_							:      List[Any]=12			,						UpperCamelCase_							:      Tuple=12			,						UpperCamelCase_							:      Optional[Any]=3_072			,						UpperCamelCase_							:      List[Any]="gelu"			,						UpperCamelCase_							:      Optional[Any]=0.1			,						UpperCamelCase_							:      Tuple=0.1			,						UpperCamelCase_							:      List[str]=512			,						UpperCamelCase_							:      List[Any]=2			,						UpperCamelCase_							:      List[str]=0.02			,						UpperCamelCase_							:      List[str]=1e-12			,						UpperCamelCase_							:      List[Any]=1			,						UpperCamelCase_							:      Optional[Any]=0			,						UpperCamelCase_							:      Any=2			,						UpperCamelCase_							:      int="absolute"			,						UpperCamelCase_							:      int=True			,						UpperCamelCase_							:      Union[str, Any]=None			,						**UpperCamelCase_							:      Tuple			,						):


         """simple docstring"""



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

         __A       =						vocab_size
         __A       =						hidden_size
         __A       =						num_hidden_layers
         __A       =						num_attention_heads
         __A       =						hidden_act
         __A       =						intermediate_size
         __A       =						hidden_dropout_prob
         __A       =						attention_probs_dropout_prob
         __A       =						max_position_embeddings
         __A       =						type_vocab_size
         __A       =						initializer_range
         __A       =						layer_norm_eps
         __A       =						position_embedding_type
         __A       =						use_cache
         __A       =						classifier_dropout


class    __lowercase   (						lowercase_	):







     '''simple docstring'''




     @property
     def 		lowerCAmelCase_  (					self							:      Dict					):


         """simple docstring"""



         if self.task == "multiple-choice":
             __A       =						{0: """batch""", 1: """choice""", 2: """sequence"""}
         else:
             __A       =						{0: """batch""", 1: """sequence"""}
         return OrderedDict(
             [
                 ("""input_ids""", dynamic_axis),
                 ("""attention_mask""", dynamic_axis),
             ]					)












from __future__ import annotations

from typing import Generic, TypeVar

__a   :							str						= TypeVar("T")


class    __lowercase   (						Generic[T]	):







     '''simple docstring'''




     def __init__(					self							:      Any			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         __A       =						data
         __A       =						self
         __A       =						0


class    __lowercase   (						Generic[T]	):







     '''simple docstring'''




     def __init__(					self							:      Optional[Any]					):


         """simple docstring"""



         __A       =						{}




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         __A       =						DisjointSetTreeNode(UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      List[Any]			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         __A       =						self.map[data]
         if elem_ref != elem_ref.parent:
             __A       =						self.find_set(elem_ref.parent.data					)
         return elem_ref.parent




     def 		lowerCAmelCase_  (					self							:      int			,						UpperCamelCase_							:      DisjointSetTreeNode[T]			,						UpperCamelCase_							:      DisjointSetTreeNode[T]					):


         """simple docstring"""



         if nodea.rank > nodea.rank:
             __A       =						nodea
         else:
             __A       =						nodea
             if nodea.rank == nodea.rank:
                 nodea.rank += 1





     def 		lowerCAmelCase_  (					self							:      Tuple			,						UpperCamelCase_							:      T			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         self.link(self.find_set(UpperCamelCase_					)			,						self.find_set(UpperCamelCase_					)					)


class    __lowercase   (						Generic[T]	):







     '''simple docstring'''




     def __init__(					self							:      Optional[int]					):


         """simple docstring"""



         __A       =						{}




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


         """simple docstring"""



         if node not in self.connections:
             __A       =						{}




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


         """simple docstring"""



         self.add_node(UpperCamelCase_					)
         self.add_node(UpperCamelCase_					)
         __A       =						weight
         __A       =						weight





     def 		lowerCAmelCase_  (					self							:      Dict					):


         """simple docstring"""



         __A       =						[]
         __A       =						set()
         for start in self.connections:
             for end in self.connections[start]:
                 if (start, end) not in seen:
                     seen.add((end, start)					)
                     edges.append((start, end, self.connections[start][end])					)
         edges.sort(key=lambda UpperCamelCase_					: x[2]					)

         # creating the disjoint set
         __A       =						DisjointSetTree[T]()
         for node in self.connections:
             disjoint_set.make_set(UpperCamelCase_					)

         # MST generation
         __A       =						0
         __A       =						0
         __A       =						GraphUndirectedWeighted[T]()
         while num_edges < len(self.connections					) - 1:
             __A     ,						__A     ,						__A       =						edges[index]
             index += 1
             __A       =						disjoint_set.find_set(UpperCamelCase_					)
             __A       =						disjoint_set.find_set(UpperCamelCase_					)
             if parent_u != parent_v:
                 num_edges += 1
                 graph.add_edge(UpperCamelCase_			,						UpperCamelCase_			,						UpperCamelCase_					)
                 disjoint_set.union(UpperCamelCase_			,						UpperCamelCase_					)
         return graph




