tf.saved_model.LoadOptions

Options for loading a SavedModel.

tf.saved_model.LoadOptions(
    allow_partial_checkpoint=False, experimental_io_device=None,
    experimental_skip_checkpoint=False
)

This function may be used in the options argument in functions that load a SavedModel (tf.saved_model.load, tf.keras.models.load_model).

Args
`allow_partial_checkpoint`	bool. Defaults to `False`. When enabled, allows the SavedModel checkpoint to not entirely match the loaded object.
`experimental_io_device`	string. Applies in a distributed setting. Tensorflow device to use to access the filesystem. If `None` (default) then for each variable the filesystem is accessed from the CPU:0 device of the host where that variable is assigned. If specified, the filesystem is instead accessed from that device for all variables. This is for example useful if you want to load from 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.
`experimental_skip_checkpoint`	bool. Defaults to `False`. If set to `True`, checkpoints will not be restored. Note that this in the majority of cases will generate an unusable model.

Class Variables
allow_partial_checkpoint	Instance of `member_descriptor`
experimental_io_device	Instance of `member_descriptor`
experimental_skip_checkpoint	Instance of `member_descriptor`

Args