tf.keras.models.save_model

View source on GitHub

Saves a model as a TensorFlow SavedModel or HDF5 file.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.models.save_model, `tf.compat.v2.keras.models.save_model`

tf.keras.models.save_model(
    model, filepath, overwrite=True, include_optimizer=True, save_format=None,
    signatures=None
)

The saved model contains:

- the model's configuration (topology)
- the model's weights
- the model's optimizer's state (if any)

Thus the saved model can be reinstantiated in the exact same state, without any of the code used for model definition or training.

SavedModel serialization (not yet added)

The SavedModel serialization path uses tf.saved_model.save to save the model and all trackable objects attached to the model (e.g. layers and variables). @tf.function-decorated methods are also saved. Additional trackable objects and functions are added to the SavedModel to allow the model to be loaded back as a Keras Model object.

Arguments
model	Keras model instance to be saved.
filepath	One of the following: String, path where to save the model h5py.File object where to save the model
overwrite	Whether we should overwrite any existing model at the target location, or instead ask the user with a manual prompt.
include_optimizer	If True, save optimizer's state together.
save_format	Either 'tf' or 'h5', indicating whether to save the model to Tensorflow SavedModel or HDF5. Defaults to 'tf' in TF 2.X, and 'h5' in TF 1.X.
signatures	Signatures to save with the SavedModel. Applicable to the 'tf' format only. Please see the signatures argument in tf.saved_model.save for details.

Raises
ImportError	If save format is hdf5, and h5py is not available.