code: 
  
  from functools import partial
  from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload
  
  import torch
  import torch.nn as nn
  import torch.types
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Any			,   _A   :				int			,   _A   :				Optional[int]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    if not inplace:
      a__						=ma + ma
    else:
      ma += ma
  
    return ma
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				str			,   _A   :				Tuple							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=-1 * len(_A							)
    a__						=list(range(len(tensor.shape[:zero_index]							)							)							)
    return tensor.permute(first_inds + [zero_index + i for i in inds]							)
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Dict			,   _A   :				List[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    return t.reshape(t.shape[:-no_dims] + (-1,)							)
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				int			,   _A   :				int			,   _A   :				Union[str, Any]			,   _A   :				List[str] = 1E-4							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=mask.expand(*value.shape							)
    return torch.sum(mask * value			,   dim=_A							) / (eps + torch.sum(_A			,   dim=_A							))
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				int			,   _A   :				Optional[int] = 2.3_125			,   _A   :				List[Any] = 21.6_875			,   _A   :				List[str] = 64							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=torch.linspace(_A			,   _A			,   no_bins - 1			,   device=pts.device							)
    a__						=torch.sqrt(torch.sum((pts.unsqueeze(-2							) - pts.unsqueeze(-3							)) ** 2			,   dim=-1							)							)
    return torch.bucketize(_A			,   _A							)
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Any			,   _A   :				List[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=dicts[0]
    a__						={}
    for k, v in first.items():
      a__						=[d[k] for d in dicts]
      if isinstance(_A			,   _A							):
        a__						=dict_multimap(_A			,   _A							)
      else:
        a__						=fn(_A							)
  
    return new_dict
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				List[str]			,   _A   :				Tuple							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=v_bins.view(((1,) * len(x.shape							)) + (len(_A							),)							)
    a__						=x[..., None] - reshaped_bins
    a__						=torch.argmin(torch.abs(_A							)			,   dim=-1							)
    return nn.functional.one_hot(_A			,   num_classes=len(_A							)							).float()
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Union[str, Any]			,   _A   :				Dict			,   _A   :				Tuple = 0			,   _A   :				Union[str, Any] = 0							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=[]
    for i, s in enumerate(data.shape[:no_batch_dims]							):
      a__						=torch.arange(_A							)
      a__						=r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape							) - i - 1)))							)
      ranges.append(_A							)
  
    a__						=[slice(_A							) for _ in range(len(data.shape							) - no_batch_dims							)]
    a__						=inds
    ranges.extend(_A							)
    # Matt note: Editing this to get around the behaviour of using a list as an array index changing
    # in recent Numpy versions
    return data[tuple(_A							)]
  
  
  lowerCamelCase     =      TypeVar('''T''')
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Any			,   _A   :				Tuple			,   _A   :				Optional[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						={}
    for k, v in dic.items():
      if isinstance(_A			,   _A							):
        a__						=dict_map(_A			,   _A			,   _A							)
      else:
        a__						=tree_map(_A			,   _A			,   _A							)
  
    return new_dict
  
  
  
  
  @overload
  def     UpperCAmelCase__       (    _A   :				Optional[int]			,   _A   :				Optional[Any]			,   _A   :				int							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    ...
  
  
  
  
  @overload
  def     UpperCAmelCase__       (    _A   :				List[Any]			,   _A   :				Optional[Any]			,   _A   :				Any							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    ...
  
  
  
  
  @overload
  def     UpperCAmelCase__       (    _A   :				int			,   _A   :				Dict			,   _A   :				Union[str, Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    ...
  
  
  
  
  @overload
  def     UpperCAmelCase__       (    _A   :				str			,   _A   :				Optional[Any]			,   _A   :				List[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    ...
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Optional[int]			,   _A   :				Dict			,   _A   :				Optional[int]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    if isinstance(_A			,   _A							):
      return dict_map(_A			,   _A			,   _A							)
    elif isinstance(_A			,   _A							):
      return [tree_map(_A			,   _A			,   _A							) for x in tree]
    elif isinstance(_A			,   _A							):
      return tuple(tree_map(_A			,   _A			,   _A							) for x in tree							)
    elif isinstance(_A			,   _A							):
      return fn(_A							)
    else:
      print(type(_A							)							)
      raise ValueError('''Not supported'''							)
  
  
  
  lowerCamelCase     =      partial(tree_map, leaf_type=torch.Tensor)
  
style_context: 
  
  import heapq
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Optional[Any]			,   _A   :				str			,   _A   :				Optional[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=[(0, start)]  # cost from start node,end node
    a__						=set()
    while heap:
      ((a__),   (a__))						=heapq.heappop(_A							)
      if u in visited:
        continue
      visited.add(_A							)
      if u == end:
        return cost
      for v, c in graph[u]:
        if v in visited:
          continue
        a__						=cost + c
        heapq.heappush(_A			,   (next_item, v)							)
    return -1
  
  
  lowerCamelCase     =      {
      '''A''': [['''B''', 2], ['''C''', 5]],
      '''B''': [['''A''', 2], ['''D''', 3], ['''E''', 1], ['''F''', 1]],
      '''C''': [['''A''', 5], ['''F''', 3]],
      '''D''': [['''B''', 3]],
      '''E''': [['''B''', 4], ['''F''', 3]],
      '''F''': [['''C''', 3], ['''E''', 3]],
  }
  lowerCamelCase     =      {
      '''B''': [['''C''', 1]],
      '''C''': [['''D''', 1]],
      '''D''': [['''F''', 1]],
      '''E''': [['''B''', 1], ['''F''', 3]],
      '''F''': [],
  }
  lowerCamelCase     =      {
      '''B''': [['''C''', 1]],
      '''C''': [['''D''', 1]],
      '''D''': [['''F''', 1]],
      '''E''': [['''B''', 1], ['''G''', 2]],
      '''F''': [],
      '''G''': [['''F''', 1]],
  }
  
  lowerCamelCase     =      dijkstra(G, '''E''', '''C''')
  print(short_distance)  # E -- 3 --> F -- 3 --> C == 6
  
  lowerCamelCase     =      dijkstra(Ga, '''E''', '''F''')
  print(short_distance)  # E -- 3 --> F == 3
  
  lowerCamelCase     =      dijkstra(Ga, '''E''', '''F''')
  print(short_distance)  # E -- 2 --> G -- 1 --> F == 3
  
  if __name__ == "__main__":
         import doctest
  
         doctest.testmod()
  