我该怎么做才能转换模型，以便只能在CPU上使用它？

Question

它是这样转换的：

with tf.Graph().as_default():
    with tf.Session() as sess:
        graph = sess.graph
        K.set_session(sess)
        K.set_learning_phase(0)
        inference_model = create_model(num_classes=num_classes)
        load_model()

        # Find output nodes
        outputs, output_node_list = get_nodes_from_model(inference_model.outputs)
        # find input nodes
        inputs, input_node_list = get_nodes_from_model(inference_model.inputs)

        generate_config()

        with sess.as_default():
            freeze_var_names = list(set(v.op.name for v in tf.global_variables()).difference(None or []))
            output_names = output_node_list or []
            output_names += [v.op.name for v in tf.global_variables()]
            input_graph_def = graph.as_graph_def()
            for node in input_graph_def.node:
                # print(node.name)
                node.device = ""
            frozen_graph = tf.compat.v1.graph_util.convert_variables_to_constants(
                sess, input_graph_def, output_names, freeze_var_names)
            trt_graph = trt.create_inference_graph(
                # frozen model
                input_graph_def=frozen_graph,
                outputs=output_node_list,
                # specify the max workspace
                max_workspace_size_bytes=500000000,
                # precision, can be "FP32" (32 floating point precision) or "FP16"
                precision_mode=precision,
                is_dynamic_op=True)
            # Finally we serialize and dump the output graph to the filesystem
            with tf.gfile.GFile(model_save_path, 'wb') as f:
                f.write(trt_graph.SerializeToString())

            print("TensorRT model is successfully stored! \n")

is_dynamic_op=True已经帮助转换了模型（现在它说已经成功存储了），但是我仍然无法将其加载到Docker TensorRT服务器中。 

我正在使用nvcr.io/nvidia/tensorflow:19.10-py3容器为TensorRT服务器转换模型和nvcr.io/nvidia/tensorrtserver:19.10-py3容器。

我有一个要在CPU上运行的.h5模型（用于GPU？）。我使用python转换了模型，看起来好像真的进行了转换，但是在docker tensorrt中运行它时，出现错误：...