tomgoldstein/loss-landscape

Health v2 · maintenance only

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3199 stars · 440 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyTorch code for visualizing the loss landscape of neural networks, from the NIPS 2018 paper 'Visualizing the Loss Landscape of Neural Nets'. It computes and plots 1D/2D loss surfaces along random directions near trained parameters, with MPI-based multi-GPU/multi-node parallelism and HDF5 output.

Use cases

• visualize the loss landscape of a pretrained neural network
• plot 1D linear interpolation between two model minimizers
• compare flatness of minima trained with different batch sizes
• render 2D loss surface plots for a CIFAR-10 model
• study how skip connections affect loss geometry

When to choose

• you have a pretrained PyTorch model and want to visualize its loss surface
• you need reproducible code for the NIPS 2018 loss landscape paper
• you want MPI-parallel loss computation across multiple GPUs or nodes

When to avoid

• you need a maintained library with recent PyTorch support - it targets PyTorch 0.4
• you want interactive visualization rather than script-generated plots
• your models are not PyTorch state_dicts for CIFAR-10-style architectures

Facets

library · maturity maintenance

data-visualization machine-learning gpu-computing deep-learning data-visualization machine-learning python pytorch loss-landscape hdf5 mpi research-code nips-2018 linux gpu

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