ksuit.initializers.previous_run_initializer
===========================================

.. py:module:: ksuit.initializers.previous_run_initializer


Classes
-------

.. autoapisummary::

   ksuit.initializers.previous_run_initializer.PreviousRunInitializer


Module Contents
---------------

.. py:class:: PreviousRunInitializer(initializer_config, **kwargs)

   Bases: :py:obj:`ksuit.initializers.base.CheckpointInitializer`


   Initializes a model from a checkpoint of a previous run (specified by the run_id), this initializers assumes that the previous run is over, and hence only loads model weights.
   When a previous run should be resumed for further training, use ResumeInitializer instead.


   .. rubric:: Example

   ```yaml
       model:
           ... # model config
           dim: 64
           initializers:
               - kind: ksuit.initializers.PreviousRunInitializer
                 model_info: ema=0.9999
                 checkpoint: latest
                 model_name: pointnet
                 run_id: 2025-11-01_8zlau
   ```

   When training, the stage name is usually "train". Checkpoint is usually "latest" or "best_loss", depending on which checkpoint you want to load. Model_info is an optional string that is used as suffix in the checkpoint filename. Model_name is the name of the model to load, which should match the model_name used in CheckpointCallback during the previous run.
   :param initializer_config: Configuration for the initializer. Implements `PreviousRunInitializerConfig` schema.
   :param \*\*kwargs: additional arguments to pass to the parent class.

   Initialize model from checkpoint.

   :param initializer_config: configuration for the initializer. Implements the `CheckpointInitializerConfig` schema.
   :param \*\*kwargs: additional arguments to pass to the parent class.


   .. py:attribute:: keys_to_remove


   .. py:attribute:: patterns_to_remove


   .. py:attribute:: patterns_to_rename


   .. py:attribute:: patterns_to_instantiate


   .. py:method:: init_weights(model, model_name = None)

      Initialize the model weights from the checkpoint.

      :param model: the model to load the weights into.