gives a heavily skewed timeline. Similarly, "IntelÂ® VTuneâ¢ Profiler"
  helps to analyze performance on Intel platforms further with
  "torch.autograd.profiler.emit_itt()".
Warning:
If you are profiling CUDA code, the first profiler that "bottleneck"
  runs (cProfile) will include the CUDA startup time (CUDA buffer
  allocation cost) in its time reporting. This should not matter if
  your bottlenecks result in code much slower than the CUDA startup
  time.
For more complicated uses of the profilers (like in a multi-GPU case),
please see https://docs.python.org/3/library/profile.html or
"torch.autograd.profiler.profile()" for more information.