Yogi adds a tiny bit of compute per step and may need slightly more memory. In practice, it's negligible for most models.
Most deep learning practitioners reach for Adam by default. But when training on tasks with noisy or sparse gradients (like GANs, reinforcement learning, or large-scale language models), Adam can sometimes struggle with sudden large gradient updates that destabilize training. yogi optimizer
Beyond Adam: Meet Yogi – The Optimizer That Tames Noisy Gradients Yogi adds a tiny bit of compute per