noether.core.initializers.base

Classes

InitializerConfig

InitializerBase

Helper class that provides a standard way to create an ABC using

Module Contents

class noether.core.initializers.base.InitializerConfig(/, **data)

Bases: pydantic.BaseModel

Parameters:

data (Any)

kind: str = None
kwargs: dict[str, Any] | None = None

Additional keyword arguments to pass to the initializer.

run_id: str

A unique identifier for the training stage. This is used to find the correct checkpoint.

stage_name: str | None = None

The name of the stage training stage if defined. When training, the stage name is usually “train”.

model_name: str | None = None

The name of the model to load. This is the model_name used in CheckpointCallback.

checkpoint_tag: str | None | dict = None

Which checkpoint to load. Checkpoint is usually “latest” or “best_loss”, or “E*_U*_S*”, depending on which checkpoint you want to load.

model_info: str | None = None

Optional string to provide additional info about the model weights in the checkpoint filename. E.g., the stored weights are the EMA, or in a different precision.

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class noether.core.initializers.base.InitializerBase(path_provider)

Bases: abc.ABC

Helper class that provides a standard way to create an ABC using inheritance.

Base class for model initializers.

Parameters:

path_provider (noether.core.providers.PathProvider) – PathProvider instance to access paths to load models from.

logger
path_provider
abstractmethod init_weights(model)

Initialize the model weights from the checkpoint.

Parameters:

model (noether.core.models.base.ModelBase) – the model to load the weights into.

Return type:

None

abstractmethod init_optimizer(model)

Initialize the optimizer for the model.

Parameters:

model (noether.core.models.base.ModelBase) – a model to initialize the optimizer for. Assumes the model has an attribute optim.

Return type:

None

init_trainer(trainer)

Initialize the trainer from the checkpoint.

By default, does nothing. Can be overridden by child classes.

Parameters:

trainer – the trainer to initialize.

Return type:

None

init_callbacks(callbacks, model)

Initialize the callbacks from the checkpoint.

By default, does nothing. Can be overridden by child classes.

Parameters:
Return type:

None

start_checkpoint()

Get the start checkpoint for the model.

By default , returns a TrainingIteration starting from zero.

Returns:

the start checkpoint for the model.

Return type:

TrainingIteration