



from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

snake_case    :						str  =						TypeVar('T')
def 	snake_case__       (					__lowercase       )		->		int:







						"""simple docstring"""

						return (position - 1) // 2
def 	snake_case__       (					__lowercase       )		->		int:







						"""simple docstring"""

						return (2 * position) + 1
def 	snake_case__       (					__lowercase       )		->		int:







						"""simple docstring"""

						return (2 * position) + 2




class 							lowerCAmelCase__  (	Generic[T]						):







					def __init__(       self      :     Dict):
											A__	:							list[tuple[T, int]]						    = []
											A__	:							dict[T, int]						    = {}
											A__	:							int						    = 0







					def __len__(       self      :     int):
											return self.elements







					def __repr__(       self      :     Union[str, Any]):
											return str(self.heap)







					def  _lowercase			(       self      :     Any):
											# Check if the priority queue is empty
											return self.elements == 0







					def  _lowercase			(       self      :     Optional[Any]			,		_A      :     T			,		_A      :     int):
											# Add an element with given priority to the queue
											self.heap.append((elem, weight))
											A__	:							Optional[Any]						    = self.elements
											self.elements += 1
											self._bubble_up(_A)







					def  _lowercase			(       self      :     Dict):
											# Remove and return the element with lowest weight (highest priority)
											if self.elements > 1:
																	self._swap_nodes(0			,		self.elements - 1)
											A__    ,       A__	:							Union[str, Any]						    = self.heap.pop()
											del self.position_map[elem]
											self.elements -= 1
											if self.elements > 0:
																	A__    ,       A__	:							str						    = self.heap[0]
																	self._bubble_down(_A)
											return elem







					def  _lowercase			(       self      :     Union[str, Any]			,		_A      :     T			,		_A      :     int):
											# Update the weight of the given key
											A__	:							Optional[int]						    = self.position_map[elem]
											A__	:							int						    = (elem, weight)
											if position > 0:
																	A__	:							Tuple						    = get_parent_position(_A)
																	A__    ,       A__	:							str						    = self.heap[parent_position]
																	if parent_weight > weight:
																							self._bubble_up(_A)
																	else:
																							self._bubble_down(_A)
											else:
																	self._bubble_down(_A)







					def  _lowercase			(       self      :     Tuple			,		_A      :     T):
											# Place a node at the proper position (upward movement) [to be used internally
											# only]
											A__	:							int						    = self.position_map[elem]
											if curr_pos == 0:
																	return None
											A__	:							List[Any]						    = get_parent_position(_A)
											A__    ,       A__	:							Dict						    = self.heap[curr_pos]
											A__    ,       A__	:							Optional[int]						    = self.heap[parent_position]
											if parent_weight > weight:
																	self._swap_nodes(_A			,		_A)
																	return self._bubble_up(_A)
											return None







					def  _lowercase			(       self      :     Union[str, Any]			,		_A      :     T):
											# Place a node at the proper position (downward movement) [to be used
											# internally only]
											A__	:							List[str]						    = self.position_map[elem]
											A__    ,       A__	:							List[Any]						    = self.heap[curr_pos]
											A__	:							List[str]						    = get_child_left_position(_A)
											A__	:							Optional[Any]						    = get_child_right_position(_A)
											if child_left_position < self.elements and child_right_position < self.elements:
																	A__    ,       A__	:							List[str]						    = self.heap[child_left_position]
																	A__    ,       A__	:							str						    = self.heap[child_right_position]
																	if child_right_weight < child_left_weight and child_right_weight < weight:
																							self._swap_nodes(_A			,		_A)
																							return self._bubble_down(_A)
											if child_left_position < self.elements:
																	A__    ,       A__	:							List[Any]						    = self.heap[child_left_position]
																	if child_left_weight < weight:
																							self._swap_nodes(_A			,		_A)
																							return self._bubble_down(_A)
											else:
																	return None
											if child_right_position < self.elements:
																	A__    ,       A__	:							Any						    = self.heap[child_right_position]
																	if child_right_weight < weight:
																							self._swap_nodes(_A			,		_A)
																							return self._bubble_down(_A)
											return None







					def  _lowercase			(       self      :     int			,		_A      :     int			,		_A      :     int):
											# Swap the nodes at the given positions
											A__	:							Optional[Any]						    = self.heap[nodea_pos][0]
											A__	:							Optional[Any]						    = self.heap[nodea_pos][0]
											A__    ,       A__	:							Tuple						    = (
											    self.heap[nodea_pos],
											    self.heap[nodea_pos],
											)
											A__	:							int						    = nodea_pos
											A__	:							List[str]						    = nodea_pos




class 							lowerCAmelCase__  (	Generic[T]						):







					def __init__(       self      :     Optional[Any]):
											A__	:							dict[T, dict[T, int]]						    = {}
											A__	:							int						    = 0







					def __repr__(       self      :     int):
											return str(self.connections)







					def __len__(       self      :     Any):
											return self.nodes







					def  _lowercase			(       self      :     Any			,		_A      :     T):
											# Add a node in the graph if it is not in the graph
											if node not in self.connections:
																	A__	:							int						    = {}
																	self.nodes += 1







					def  _lowercase			(       self      :     List[Any]			,		_A      :     T			,		_A      :     T			,		_A      :     int):
											# Add an edge between 2 nodes in the graph
											self.add_node(_A)
											self.add_node(_A)
											A__	:							str						    = weight
											A__	:							str						    = weight




def 	snake_case__       (					__lowercase							,     )		->		tuple[dict[T, int], dict[T, T | None]]:







						"""simple docstring"""

						A__	:							dict[T, int]						    = {node: maxsize for node in graph.connections}
						A__	:							dict[T, T | None]						    = {node: None for node in graph.connections}

						A__	:							MinPriorityQueue[T]						    = MinPriorityQueue()
						for node, weight in dist.items():
												priority_queue.push(__lowercase							,     __lowercase       )

						if priority_queue.is_empty():
												return dist, parent

						# initialization
						A__	:							int						    = priority_queue.extract_min()
						A__	:							str						    = 0
						for neighbour in graph.connections[node]:
												if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
																		A__	:							List[str]						    = dist[node] + graph.connections[node][neighbour]
																		priority_queue.update_key(__lowercase							,     dist[neighbour]       )
																		A__	:							Optional[Any]						    = node

    # running prim's algorithm
						while not priority_queue.is_empty():
												A__	:							Union[str, Any]						    = priority_queue.extract_min()
												for neighbour in graph.connections[node]:
																		if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
																								A__	:							int						    = dist[node] + graph.connections[node][neighbour]
																								priority_queue.update_key(__lowercase							,     dist[neighbour]       )
																								A__	:							Any						    = node
						return dist, parent




from collections import OrderedDict
from typing import Mapping

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


snake_case    :						Optional[int]  =						logging.get_logger(__name__)

snake_case    :						Union[str, Any]  =						{
    'facebook/data2vec-text-base': 'https://huggingface.co/data2vec/resolve/main/config.json',
}




class 							lowerCAmelCase__  (	UpperCamelCase						):
					__A     :    Optional[Any]           =						'data2vec-text'







					def __init__(       self      :     Optional[Any]			,		_A      :     List[str]=3_0522			,		_A      :     Optional[int]=768			,		_A      :     Union[str, Any]=12			,		_A      :     str=12			,		_A      :     Optional[int]=3072			,		_A      :     Dict="gelu"			,		_A      :     List[str]=0.1			,		_A      :     Any=0.1			,		_A      :     str=512			,		_A      :     Any=2			,		_A      :     str=0.02			,		_A      :     List[str]=1e-12			,		_A      :     Optional[int]=1			,		_A      :     Any=0			,		_A      :     Any=2			,		_A      :     List[Any]="absolute"			,		_A      :     Tuple=True			,		_A      :     str=None			,		**_A      :     List[Any]			,		):
											super().__init__(pad_token_id=_A			,		bos_token_id=_A			,		eos_token_id=_A			,		**_A)

											A__	:							Optional[int]						    = vocab_size
											A__	:							Tuple						    = hidden_size
											A__	:							str						    = num_hidden_layers
											A__	:							Union[str, Any]						    = num_attention_heads
											A__	:							Dict						    = hidden_act
											A__	:							List[Any]						    = intermediate_size
											A__	:							int						    = hidden_dropout_prob
											A__	:							Dict						    = attention_probs_dropout_prob
											A__	:							Union[str, Any]						    = max_position_embeddings
											A__	:							Tuple						    = type_vocab_size
											A__	:							Union[str, Any]						    = initializer_range
											A__	:							str						    = layer_norm_eps
											A__	:							int						    = position_embedding_type
											A__	:							str						    = use_cache
											A__	:							int						    = classifier_dropout




class 							lowerCAmelCase__  (	UpperCamelCase						):







					@property
					def  _lowercase			(       self      :     Tuple):
											if self.task == "multiple-choice":
																	A__	:							List[str]						    = {0: "batch", 1: "choice", 2: "sequence"}
											else:
																	A__	:							List[str]						    = {0: "batch", 1: "sequence"}
											return OrderedDict(
											    [
											        ("input_ids", dynamic_axis),
											        ("attention_mask", dynamic_axis),
											    ])