monkeypatch.relora
monkeypatch.relora
Implements the ReLoRA training procedure from https://arxiv.org/abs/2307.05695, minus the initial full fine-tune.
Classes
| Name | Description |
|---|---|
| ReLoRACallback | Callback to merge LoRA weights into the base model and save full-weight checkpoints |
ReLoRACallback
monkeypatch.relora.ReLoRACallback(cfg)Callback to merge LoRA weights into the base model and save full-weight checkpoints
Functions
| Name | Description |
|---|---|
| magnitude_pruning_ | Zero the lowest prune_ratio fraction of values by absolute magnitude, in place. |
| random_pruning_ | Zero a random prune_ratio fraction of values, in place. |
| reset_optimizer | Prune optimizer state for reset_params only. |
magnitude_pruning_
monkeypatch.relora.magnitude_pruning_(tensor, prune_ratio)Zero the lowest prune_ratio fraction of values by absolute magnitude, in place.
random_pruning_
monkeypatch.relora.random_pruning_(tensor, prune_ratio)Zero a random prune_ratio fraction of values, in place.
reset_optimizer
monkeypatch.relora.reset_optimizer(
optimizer,
*,
reset_params,
optimizer_state_keys,
prune_method='magnitude',
prune_ratio=0.9,
)Prune optimizer state for reset_params only.