!!install!! - Loss Scaling Download

scaled_loss = scaling_factor * loss

# scaler.step() first unscales the gradients of the optimizer's assigned params. scaler.step(optimizer) loss scaling download

: Loss scaling preserves small gradients that would otherwise vanish in FP16. scaled_loss = scaling_factor * loss # scaler

| Method | Description | Best for | |--------|-------------|-----------| | | User chooses a fixed scale (e.g., 128) | Stable models, quick prototyping | | Dynamic loss scaling | Starts high, reduces automatically if overflow detected | Most production training (PyTorch AMP, NVIDIA Apex) | | Automatic mixed precision (AMP) | Combines dynamic scaling + automatic op casting | Default modern approach | 128) | Stable models

# Enable loss scaling with a scaling factor of 128 scaling_factor = 128