Name scopes are not needed.
By default, variables are
associated with the loaded
object and function names
are deduped.
saver_kwargs
Not supported
-
Before & After Usage Example
Before:
with tf.compat.v1.Session(graph=tf.Graph()) as sess:
tf.compat.v1.saved_model.loader.load(sess, ["foo-tag"], export_dir)
After:
model = tf.saved_model.load(export_dir, tags=["foo-tag"])
Description
Args
sess
The TensorFlow session to restore the variables.
tags
Set of string tags to identify the required MetaGraphDef. These should
correspond to the tags used when saving the variables using the
SavedModel save() API.
export_dir
Directory in which the SavedModel protocol buffer and variables
to be loaded are located.
import_scope
Optional string -- if specified, prepend this string
followed by '/' to all loaded tensor names. This scope is applied to
tensor instances loaded into the passed session, but it is not written
through to the static MetaGraphDef protocol buffer that is returned.
**saver_kwargs
Optional keyword arguments passed through to Saver.
Returns
The MetaGraphDef protocol buffer loaded in the provided session. This
can be used to further extract signature-defs, collection-defs, etc.
Raises
RuntimeError
MetaGraphDef associated with the tags cannot be found.