with_detect_anomaly: Context-manager that enable anomaly detection for the...

In torch: Tensors and Neural Networks with 'GPU' Acceleration

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()
  })
})
}

torch documentation built on May 29, 2024, 9:54 a.m.