tf.train.CheckpointManager | TensorFlow v2.0.0 (original) (raw)
tf.train.CheckpointManager
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Deletes old checkpoints.
View aliases
Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.train.CheckpointManager
tf.train.CheckpointManager(
checkpoint, directory, max_to_keep, keep_checkpoint_every_n_hours=None,
checkpoint_name='ckpt'
)
Example usage:
import tensorflow as tf
checkpoint = tf.train.Checkpoint(optimizer=optimizer, model=model)
manager = tf.contrib.checkpoint.CheckpointManager(
checkpoint, directory="/tmp/model", max_to_keep=5)
status = checkpoint.restore(manager.latest_checkpoint)
while True:
# train
manager.save()
CheckpointManager preserves its own state across instantiations (see the__init__ documentation for details). Only one should be active in a particular directory at a time.
| Args | |
|---|---|
| checkpoint | The tf.train.Checkpoint instance to save and manage checkpoints for. |
| directory | The path to a directory in which to write checkpoints. A special file named "checkpoint" is also written to this directory (in a human-readable text format) which contains the state of theCheckpointManager. |
| max_to_keep | An integer, the number of checkpoints to keep. Unless preserved by keep_checkpoint_every_n_hours, checkpoints will be deleted from the active set, oldest first, until only max_to_keepcheckpoints remain. If None, no checkpoints are deleted and everything stays in the active set. Note that max_to_keep=None will keep all checkpoint paths in memory and in the checkpoint state protocol buffer on disk. |
| keep_checkpoint_every_n_hours | Upon removal from the active set, a checkpoint will be preserved if it has been at leastkeep_checkpoint_every_n_hours since the last preserved checkpoint. The default setting of None does not preserve any checkpoints in this way. |
| checkpoint_name | Custom name for the checkpoint file. |
| Raises | |
|---|---|
| ValueError | If max_to_keep is not a positive integer. |
| Attributes | |
|---|---|
| checkpoints | A list of managed checkpoints.Note that checkpoints saved due to keep_checkpoint_every_n_hours will not show up in this list (to avoid ever-growing filename lists). |
| latest_checkpoint | The prefix of the most recent checkpoint in directory.Equivalent to tf.train.latest_checkpoint(directory) where directory is the constructor argument to CheckpointManager. Suitable for passing to tf.train.Checkpoint.restore to resume training. |
Methods
save
save(
checkpoint_number=None
)
Creates a new checkpoint and manages it.
| Args | |
|---|---|
| checkpoint_number | An optional integer, or an integer-dtype Variable orTensor, used to number the checkpoint. If None (default), checkpoints are numbered using checkpoint.save_counter. Even ifcheckpoint_number is provided, save_counter is still incremented. A user-provided checkpoint_number is not incremented even if it is aVariable. |
| Returns |
|---|
| The path to the new checkpoint. It is also recorded in the checkpointsand latest_checkpoint properties. |