|View source on GitHub|
Options for saving to SavedModel.
Compat aliases for migration
See Migration guide for more details.
tf.saved_model.SaveOptions( namespace_whitelist=None, save_debug_info=False, function_aliases=None, experimental_io_device=None, experimental_variable_policy=None )
Used in the notebooks
|Used in the tutorials|
||List of strings containing op namespaces to whitelist when saving a model. Saving an object that uses namespaced ops must explicitly add all namespaces to the whitelist. The namespaced ops must be registered into the framework when loading the SavedModel.|
||Boolean indicating whether debug information is saved. If True, then a debug/saved_model_debug_info.pb file will be written with the contents of a GraphDebugInfo binary protocol buffer containing stack trace information for all ops and functions that are saved.|
Python dict. Mapping from string to object returned by
@tf.function. A single tf.function can generate many ConcreteFunctions.
If a downstream tool wants to refer to all concrete functions generated
by a single tf.function you can use the
string. Applies in a distributed setting.
Tensorflow device to use to access the filesystem. If
This is for example useful if you want to save to a local directory, such as "/tmp" when running in a distributed setting. In that case pass a device for the host where the "/tmp" directory is accessible.
The policy to apply to variables when
saving. This is either a