PyTorch Debugger-PyTorch Code Debugging Tool

Example

Inspecting the gradients of a specific layer in a deep neural network to troubleshoot vanishing or exploding gradients.

Scenario

During training, a developer notices that the model's performance plateaus prematurely. By inspecting gradients, the developer identifies that gradients for early layers are significantly smaller, indicating vanishing gradients.

Example

Identifying bottlenecks in model inference time, such as slow operations or data transfer issues.

Scenario

A developer is tasked with deploying a model for real-time inference. Using performance profiling, they discover a particular convolution operation is the bottleneck due to inefficient use of memory bandwidth.

Example

Tracking down a memory leak that causes out-of-memory errors during the training of large models.

Scenario

While training a large-scale image processing model, a developer encounters repeated out-of-memory errors. By employing memory leak detection, they pinpoint the issue to a loop that inadvertently retains references to intermediate tensors.