What is the Tensorflow Java Api `toGraphDef` equivalent in Python?

I am using the Tensorflow Java Api to load an already created Tensorflow model into the JVM. I am using this as an example: tensorflow/examples/LabelImage.java

Here is my simple scala code:

import java.nio.file.{Files, Path, Paths}
import org.tensorflow.{Graph, Session, Tensor}

def readAllBytesOrExit(path: Path): Array[Byte] = Files.readAllBytes(path)
val graphDef = readAllBytesOrExit(Paths.get("PATH_TO_A_SINGLE_FILE_DESCRIBING_TF_MODEL.pb"))
val g = new Graph()
g.importGraphDef(graphDef)
val session = new Session(g)
val result: Tensor = session.runner().feed("input", image).fetch("output").run().get(0))

How do I save my model to get both the Session and the Graph stored in the same file. as described in the "PATH_TO_A_SINGLE_FILE_DESCRIBING_TF_MODEL.pb" above.

Described here it mentions:

The serialized representation of the graph, often referred to as a GraphDef, can be generated by toGraphDef() and equivalents in other language APIs.

What are the equivalents in other language APIs? I dont find it obvious

Note: I already looked at the mnist_saved_model.py under tensorflow_serving but saving it through that procedure gives me a .pb file and a variables folder. When trying to load that .pb file I get: java.lang.IllegalArgumentException: Invalid GraphDef

Copyright License：
Author:「Daniel Hasegan」,Reproduced under the CC 4.0 BY-SA copyright license with link to original source & disclaimer.
Link to：https://stackoverflow.com/questions/43242857/what-is-the-tensorflow-java-api-tographdef-equivalent-in-python