record_function

torch.autograd.profiler.record_function(name, args=None)[源代码]

一个上下文管理器和函数装饰器,用于在运行自动梯度分析仪时为代码块或函数添加标签。只有在启用CPU活动跟踪时,这些标签才会显示出来。

在分析代码性能时非常有用。

参数
  • name (str) – 代码块的名称标签。

  • node_id (int) – 节点的ID,用于分布式分析。默认不设置。

  • 情况非分布式):

示例

>>> x = torch.randn((1, 1), requires_grad=True)
>>> with torch.autograd.profiler.profile() as prof:
...     y = x ** 2
...     with torch.autograd.profiler.record_function("label-z"): # label the block
...         z = y ** 3
...     y.backward()
...
>>> # NOTE: some columns were removed for brevity
>>> print(prof.key_averages().table(sort_by="self_cpu_time_total"))
-----------------------------------  ---------------  ---------------  ---------------
Name                                 Self CPU total %  CPU time avg     Number of Calls
-----------------------------------  ---------------  ---------------  ---------------
pow                                  60.77%           47.470us         3
mul                                  21.73%           25.465us         2
PowBackward0                         12.03%           121.891us        1
torch::autograd::AccumulateGrad      2.70%            6.324us          1
label-z                              2.13%            12.421us         1
torch::autograd::GraphRoot           0.64%            1.503us          1
-----------------------------------  ---------------  ---------------  ---------------
Self CPU time total: 234.344us
CUDA time total: 0.000us
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