



'''simple docstring'''





from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

lowercase_		       =  TypeVar("T")




def lowerCAmelCase  (__A):



     """simple docstring"""



     return (position - 1) // 2




def lowerCAmelCase  (__A):



     """simple docstring"""



     return (2 * position) + 1




def lowerCAmelCase  (__A):



     """simple docstring"""



     return (2 * position) + 2






class __A			(  Generic[T]						):



 '''simple docstring'''







 def __init__(self       )    ->     None:


      """simple docstring"""



      _a      =  []
      _a      =  {}
      _a      =  0



 def __len__(self       )    ->     int:


      """simple docstring"""



      return self.elements



 def __repr__(self       )    ->     str:


      """simple docstring"""



      return str(self.heap       )



 def 					a__  (self       )    ->     bool:


      """simple docstring"""



      return self.elements == 0



 def 					a__  (self ,   A ,   A       )    ->     None:


      """simple docstring"""



      self.heap.append((elem, weight)       )
      _a      =  self.elements
      self.elements += 1
      self._bubble_up(A       )



 def 					a__  (self       )    ->     T:


      """simple docstring"""



      if self.elements > 1:
           self._swap_nodes(0 ,   self.elements - 1       )
      _a  ,    _a      =  self.heap.pop()
      del self.position_map[elem]
      self.elements -= 1
      if self.elements > 0:
           _a  ,    _a      =  self.heap[0]
           self._bubble_down(A       )
      return elem



 def 					a__  (self ,   A ,   A       )    ->     None:


      """simple docstring"""



      _a      =  self.position_map[elem]
      _a      =  (elem, weight)
      if position > 0:
           _a      =  get_parent_position(A       )
           _a  ,    _a      =  self.heap[parent_position]
           if parent_weight > weight:
                self._bubble_up(A       )
           else:
                self._bubble_down(A       )
      else:
           self._bubble_down(A       )



 def 					a__  (self ,   A       )    ->     None:


      """simple docstring"""



      _a      =  self.position_map[elem]
      if curr_pos == 0:
           return None
      _a      =  get_parent_position(A       )
      _a  ,    _a      =  self.heap[curr_pos]
      _a  ,    _a      =  self.heap[parent_position]
      if parent_weight > weight:
           self._swap_nodes(A ,   A       )
           return self._bubble_up(A       )
      return None



 def 					a__  (self ,   A       )    ->     None:


      """simple docstring"""



      _a      =  self.position_map[elem]
      _a  ,    _a      =  self.heap[curr_pos]
      _a      =  get_child_left_position(A       )
      _a      =  get_child_right_position(A       )
      if child_left_position < self.elements and child_right_position < self.elements:
           _a  ,    _a      =  self.heap[child_left_position]
           _a  ,    _a      =  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      =  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      =  self.heap[child_right_position]
           if child_right_weight < weight:
                self._swap_nodes(A ,   A       )
                return self._bubble_down(A       )
      return None



 def 					a__  (self ,   A ,   A       )    ->     None:


      """simple docstring"""



      _a      =  self.heap[nodea_pos][0]
      _a      =  self.heap[nodea_pos][0]
      _a  ,    _a      =  (
          self.heap[nodea_pos],
          self.heap[nodea_pos],
      )
      _a      =  nodea_pos
      _a      =  nodea_pos






class __A			(  Generic[T]						):



 '''simple docstring'''







 def __init__(self       )    ->     None:


      """simple docstring"""



      _a      =  {}
      _a      =  0



 def __repr__(self       )    ->     str:


      """simple docstring"""



      return str(self.connections       )



 def __len__(self       )    ->     int:


      """simple docstring"""



      return self.nodes



 def 					a__  (self ,   A       )    ->     None:


      """simple docstring"""



      if node not in self.connections:
           _a      =  {}
           self.nodes += 1



 def 					a__  (self ,   A ,   A ,   A       )    ->     None:


      """simple docstring"""



      self.add_node(A       )
      self.add_node(A       )
      _a      =  weight
      _a      =  weight





def lowerCAmelCase  (__A  ,	):



     """simple docstring"""



     _a      =  {node: maxsize for node in graph.connections}
     _a      =  {node: None for node in graph.connections}

     _a      =  MinPriorityQueue()
     for node, weight in dist.items():
          priority_queue.push(__A  ,	__A)

     if priority_queue.is_empty():
          return dist, parent

     # initialization
     _a      =  priority_queue.extract_min()
     _a      =  0
     for neighbour in graph.connections[node]:
          if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
               _a      =  dist[node] + graph.connections[node][neighbour]
               priority_queue.update_key(__A  ,	dist[neighbour])
               _a      =  node

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








'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


lowercase_		       =  logging.get_logger(__name__)

lowercase_		       =  {
    "facebook/xmod-base": "https://huggingface.co/facebook/xmod-base/resolve/main/config.json",
    "facebook/xmod-large-prenorm": "https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json",
    "facebook/xmod-base-13-125k": "https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json",
    "facebook/xmod-base-30-125k": "https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json",
    "facebook/xmod-base-30-195k": "https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json",
    "facebook/xmod-base-60-125k": "https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json",
    "facebook/xmod-base-60-265k": "https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json",
    "facebook/xmod-base-75-125k": "https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json",
    "facebook/xmod-base-75-269k": "https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json",
}






class __A			(  A						):



 '''simple docstring'''







 __lowerCamelCase    :       Any          =       'xmod'



 def __init__(self ,   A=30_522 ,   A=768 ,   A=12 ,   A=12 ,   A=3_072 ,   A="gelu" ,   A=0.1 ,   A=0.1 ,   A=512 ,   A=2 ,   A=0.02 ,   A=1E-12 ,   A=1 ,   A=0 ,   A=2 ,   A="absolute" ,   A=True ,   A=None ,   A=False ,   A=2 ,   A=False ,   A=True ,   A=True ,   A=("en_XX",) ,   A=None ,   **A ,   )    ->     List[str]:


      """simple docstring"""



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

      _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
      _a      =  pre_norm
      _a      =  adapter_reduction_factor
      _a      =  adapter_layer_norm
      _a      =  adapter_reuse_layer_norm
      _a      =  ln_before_adapter
      _a      =  list(A       )
      _a      =  default_language






class __A			(  A						):



 '''simple docstring'''







 @property
 def 					a__  (self       )    ->     Mapping[str, Mapping[int, str]]:


      """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),
          ]       )



