with_detect_anomaly {torch} | R Documentation |
Context-manager that enable anomaly detection for the autograd engine.
Description
This does two things:
Usage
with_detect_anomaly(code)
Arguments
code |
Code that will be executed in the detect anomaly context. |
Details
Running the forward pass with detection enabled will allow the backward pass to print the traceback of the forward operation that created the failing backward function.
Any backward computation that generate "nan" value will raise an error.
Warning
This mode should be enabled only for debugging as the different tests will slow down your program execution.
Examples
if (torch_is_installed()) {
x <- torch_randn(2, requires_grad = TRUE)
y <- torch_randn(1)
b <- (x^y)$sum()
y$add_(1)
try({
b$backward()
with_detect_anomaly({
b$backward()
})
})
}
[Package torch version 0.13.0 Index]