





'''simple docstring'''


import functools
import gc
import inspect

import torch

from .imports import is_npu_available, is_xpu_available
def 							UpperCAmelCase_  (						*__lowerCamelCase : Union[str, Any]			):





   if not isinstance(__lowerCAmelCase     ,__lowerCAmelCase			):
      lowercase_      :int         =			list(__lowerCAmelCase			)
   for i in range(len(__lowerCAmelCase			)			):
      lowercase_      :Union[str, Any]         =			None
   gc.collect()
   if is_xpu_available():
      torch.xpu.empty_cache()
   elif is_npu_available():
      torch.npu.empty_cache()
   else:
      torch.cuda.empty_cache()
   return objects
def 							UpperCAmelCase_  (						__lowerCamelCase : Union[str, Any]			):
   lowercase_      :Tuple         =			[
       '''CUDA out of memory.''',  # CUDA OOM
       '''cuDNN error: CUDNN_STATUS_NOT_SUPPORTED.''',  # CUDNN SNAFU
       '''DefaultCPUAllocator: can\'t allocate memory''',  # CPU OOM
   ]
   if isinstance(__lowerCAmelCase     ,__lowerCAmelCase			) and len(exception.args			) == 1:
      return any(err in exception.args[0] for err in _statements			)
   return False


def 							UpperCAmelCase_  (						__lowerCamelCase : Any = None     ,__lowerCamelCase : Tuple = 1_28			):





   if function is None:
      return functools.partial(__lowerCAmelCase     ,starting_batch_size=__lowerCAmelCase			)

   lowercase_      :List[Any]         =			starting_batch_size

   def decorator(*__lowerCamelCase : List[str]     ,**__lowerCamelCase : List[Any]			):
      nonlocal batch_size
      gc.collect()
      if is_xpu_available():
         torch.xpu.empty_cache()
      elif is_npu_available():
         torch.npu.empty_cache()
      else:
         torch.cuda.empty_cache()
      lowercase_      :Union[str, Any]         =			list(inspect.signature(__lowerCAmelCase			).parameters.keys()			)
      # Guard against user error
      if len(__lowerCAmelCase			) < (len(__lowerCAmelCase			) + 1):
         lowercase_      :Union[str, Any]         =			''', '''.join([F'{arg}={value}' for arg, value in zip(params[1:]     ,args[1:]			)]			)
         raise TypeError(
             F'Batch size was passed into `{function.__name__}` as the first argument when called.'
             F'Remove this as the decorator already does so: `{function.__name__}({arg_str})`'			)
      while True:
         if batch_size == 0:
            raise RuntimeError("No executable batch size found, reached zero."			)
         try:
            return function(__lowerCAmelCase     ,*__lowerCAmelCase     ,**__lowerCAmelCase			)
         except Exception as e:
            if should_reduce_batch_size(__lowerCAmelCase			):
               gc.collect()
               if is_xpu_available():
                  torch.xpu.empty_cache()
               elif is_npu_available():
                  torch.npu.empty_cache()
               else:
                  torch.cuda.empty_cache()
               batch_size //= 2
            else:
               raise

   return decorator









'''simple docstring'''


from __future__ import annotations

lowerCAmelCase :					Any 							={
    '''A''': ['''B''', '''C''', '''E'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F''', '''G'''],
    '''D''': ['''B'''],
    '''E''': ['''A''', '''B''', '''D'''],
    '''F''': ['''C'''],
    '''G''': ['''C'''],
}
class 				a_       :





     def __init__(			self		: List[Any]     ,				lowercase		: dict[str, list[str]]     ,				lowercase		: str						):





        """simple docstring"""




        lowercase_      :List[str]         =			graph
        # mapping node to its parent in resulting breadth first tree
        lowercase_      :dict[str, str | None]         =			{}
        lowercase_      :Dict         =			source_vertex





     def 							lowercase__				(			self		: Tuple						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			{self.source_vertex}
        lowercase_      :Tuple         =			None
        lowercase_      :Dict         =			[self.source_vertex]  # first in first out queue

        while queue:
           lowercase_      :int         =			queue.pop(0						)
           for adjacent_vertex in self.graph[vertex]:
              if adjacent_vertex not in visited:
                 visited.add(lowercase						)
                 lowercase_      :Optional[Any]         =			vertex
                 queue.append(lowercase						)







     def 							lowercase__				(			self		: Tuple     ,				lowercase		: str						):





        """simple docstring"""




        if target_vertex == self.source_vertex:
           return self.source_vertex

        lowercase_      :List[str]         =			self.parent.get(lowercase						)
        if target_vertex_parent is None:
           lowercase_      :Union[str, Any]         =			(
               F'No path from vertex: {self.source_vertex} to vertex: {target_vertex}'
           )
           raise ValueError(lowercase						)

        return self.shortest_path(lowercase						) + F'->{target_vertex}'


if __name__ == "__main__":
 lowerCAmelCase :					Dict 							=Graph(graph, '''G''')
 g.breath_first_search()
 print(g.shortest_path('''D'''))
 print(g.shortest_path('''G'''))
 print(g.shortest_path('''Foo'''))


