orbit.actions.SaveCheckpointIfPreempted
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Action that saves on-demand checkpoints after a preemption.
orbit.actions.SaveCheckpointIfPreempted(
cluster_resolver: tf.distribute.cluster_resolver.ClusterResolver,
checkpoint_manager: tf.train.CheckpointManager,
checkpoint_number: Optional[tf.Variable] = None,
keep_running_after_save: Optional[bool] = False
)
Args |
|---|
cluster_resolver
|
A tf.distribute.cluster_resolver.ClusterResolver
object.
|
checkpoint_manager
|
A tf.train.CheckpointManager object.
|
checkpoint_number
|
A tf.Variable to indicate the checkpoint_number for
checkpoint manager, usually it will be the global step.
|
keep_running_after_save
|
Whether to keep the job running after the
preemption on-demand checkpoint. Only set to True when in-process
preemption recovery with tf.distribute.experimental.PreemptionWatcher is
enabled.
|
Methods
__call__
View source
__call__(
_
) -> None
Call self as a function.
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Last updated 2025-04-18 UTC.
[null,null,["Last updated 2025-04-18 UTC."],[],[],null,["# orbit.actions.SaveCheckpointIfPreempted\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/models/blob/v2.19.1/orbit/actions/save_checkpoint_if_preempted.py#L22-L62) |\n\nAction that saves on-demand checkpoints after a preemption. \n\n orbit.actions.SaveCheckpointIfPreempted(\n cluster_resolver: tf.distribute.cluster_resolver.ClusterResolver,\n checkpoint_manager: tf.train.CheckpointManager,\n checkpoint_number: Optional[tf.Variable] = None,\n keep_running_after_save: Optional[bool] = False\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `cluster_resolver` | A [`tf.distribute.cluster_resolver.ClusterResolver`](https://www.tensorflow.org/api_docs/python/tf/distribute/cluster_resolver/ClusterResolver) object. |\n| `checkpoint_manager` | A [`tf.train.CheckpointManager`](https://www.tensorflow.org/api_docs/python/tf/train/CheckpointManager) object. |\n| `checkpoint_number` | A [`tf.Variable`](https://www.tensorflow.org/api_docs/python/tf/Variable) to indicate the checkpoint_number for checkpoint manager, usually it will be the global step. |\n| `keep_running_after_save` | Whether to keep the job running after the preemption on-demand checkpoint. Only set to True when in-process preemption recovery with tf.distribute.experimental.PreemptionWatcher is enabled. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `__call__`\n\n[View source](https://github.com/tensorflow/models/blob/v2.19.1/orbit/actions/save_checkpoint_if_preempted.py#L59-L62) \n\n __call__(\n _\n ) -\u003e None\n\nCall self as a function."]]
View source on GitHub