39a106e526e70b5d64bf9f5404311eb490df6ea5,inference_worker.py,,main,#,32

Before Change

        batch_size=server_config.batch_size,
        descriptor_path=FLAGS.descriptor)

    n = dual_net.DualNetwork(FLAGS.model, worker_config)

    outputs = {
        "features": n.sess.graph.get_tensor_by_name("unflatten_features:0"),
        "dummy": n.sess.graph.get_tensor_by_name("put_outputs:0"),
    }
    output = n.sess.run(outputs)

    for f in output["features"]:
        print("---------------------------")
        for r in range(go.N):
            row = ""

After Change

    sess = tf.Session(graph=tf.Graph(), config=config)
    with sess.graph.as_default():
        loop = dual_net.model_inference_worker_fn(worker_config)
        tf.train.Saver().restore(sess, FLAGS.model)

    print("running graph")
    sess.run(loop)

Instances