CheckpointIO¶
- class lightning.fabric.plugins.io.checkpoint_io.CheckpointIO[source]¶
Bases:
ABC
Interface to save/load checkpoints as they are saved through the
Strategy
.Warning
This is an experimental feature.
Typically most plugins either use the Torch based IO Plugin;
TorchCheckpointIO
but may require particular handling depending on the plugin.In addition, you can pass a custom
CheckpointIO
by extending this class and passing it to the Trainer, i.eTrainer(plugins=[MyCustomCheckpointIO()])
.Note
For some plugins, it is not possible to use a custom checkpoint plugin as checkpointing logic is not modifiable.
- abstract load_checkpoint(path, map_location=None, weights_only=None)[source]¶
Load checkpoint from a path when resuming or loading ckpt for test/validate/predict stages.
- Parameters:
map_location¶ (
Optional
[Any
]) – a function,torch.device
, string or a dict specifying how to remap storage locations.weights_only¶ (
Optional
[bool
]) – Defaults toNone
. IfTrue
, restricts loading tostate_dicts
of plaintorch.Tensor
and other primitive types. If loading a checkpoint from a trusted source that contains annn.Module
, useweights_only=False
. If loading checkpoint from an untrusted source, we recommend usingweights_only=True
. For more information, please refer to the PyTorch Developer Notes on Serialization Semantics.
- Return type:
Returns: The loaded checkpoint.