jettify/pytorch-optimizer

Health v2 · maintenance only

Adoption not part of the score

3171 stars · 307 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

torch-optimizer is a Python library providing a collection of additional optimization algorithms for PyTorch, drop-in compatible with the torch.optim module. It implements optimizers like DiffGrad, AdaBound, Lamb, Yogi, Lookahead, Shampoo, and many others from recent research papers.

Use cases

• find alternative optimizers for pytorch model training
• use adabound or lamb optimizer in pytorch
• compare optimization algorithms for deep learning experiments
• install extra optimizers not included in torch.optim
• speed up neural network convergence with newer optimizers

When to choose

• you need research optimizers like DiffGrad, AdaBound, Lamb, or Lookahead in PyTorch
• you want a drop-in replacement API compatible with torch.optim
• you are benchmarking different optimization algorithms

When to avoid

• standard SGD or Adam suffices for your training
• you work in TensorFlow or JAX rather than PyTorch
• you need actively developed optimizers with frequent updates

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning deep-learning developer-tools python pytorch optimizers gradient-descent adam-variants training

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