记录函数 ¶

类 torch.autograd.profiler.record_function(name, args=None)[source][source] ¶

自动微分分析器运行时，为代码块/函数添加标签的上下文管理器/函数装饰器。标签仅在启用 CPU 活动跟踪时显示。

追踪代码性能时很有用。

参数:

• name (str) – 分配给代码块的标签。

• node_id (int) – 节点 ID，用于分布式分析。非分布式（non-distributed）情况下未设置。

• 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