record_function

class torch.autograd.profiler.record_function(name, args=None)

上下文管理器/函数装饰器，在运行 autograd 分析器时向代码块/函数添加标签。仅当启用 CPU 活动跟踪时，标签才会显示。

在跟踪代码配置文件时很有用。

参数

• name (str) – 分配给代码块的标签。

• node_id (int) – 节点的 ID，用于分布式分析。在

• 案例中未设置。 (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