class_docstr: Profiling information about a single function.
class_docstr_tok: ["Profiling","information","about","a","single","function","."]
code: def self_privateuse1_time_total(self):
      if self.is_async or not self.use_device:
          return 0
      if self.device_type == DeviceType.CPU:
          return self.privateuse1_time_total - sum(
              [
                  child.privateuse1_time_total
                  for child in self.cpu_children
              ]
          )
      else:
          assert self.device_type == DeviceType.CUDA
          return self.privateuse1_time_total
  
imports: import bisect
  import itertools
  import math
  from collections import defaultdict, namedtuple
  from operator import attrgetter
  from typing import Any, Dict, List, Optional, Tuple
  import torch
  from torch.autograd import DeviceType
label_desc: Use image node_id 12 for calling the FunctionEvent obj's underlying member method code with example usage: obj.self_privateuse1_time_total() and returns: int, unknown, self