Load TensorFlow saved model and run inference.

load_saved_model.py

import tensorflow as tf

MODEL_PATH = '/home/robin/Desktop/arc_inf/1554262166'
IMAGE_PATH = '/data/dataset/public/ms_celeb_1m/arc_face_data/img/0/0.jpg'

with tf.Session(graph=tf.Graph()) as sess:
    # Restore model from the saved_modle file, that is exported by TensorFlow estimator.
    tf.saved_model.loader.load(sess, ["serve"], MODEL_PATH)

    # Get the output node from the graph.
    graph = tf.get_default_graph()
    output = graph.get_tensor_by_name('embeddings:0')

    # Read in images to be processed. The image should be in size of 112x112x3.
    with open(IMAGE_PATH, 'rb') as f:
        _img_bytes = f.read()

    # Run forward pass with images.
    embd = sess.run(output, feed_dict={'input_tensor:0': [_img_bytes]})

    # Print out the result.
    print(embd[0])