959372edab3020c0164b8a2da4aaff1c49ba8400,example/resnet/convert_resnet_keras.py,,main,#,15

Before Change

    args = parser.parse_args()
    keras_model_path = path.join(args.out, "resnet50.h5")

    if not os.path.exists(keras_model_path):
        console.stderr("Exporting Keras model into file")
        os.makedirs(args.out, exist_ok=True)
        model = resnet50.ResNet50(include_top=True, weights="imagenet")
        model.save(keras_model_path)

    console.stderr("Converting model into WebDNN format (graph descriptor)")
    // only for demo purpose, maybe not safe
    convert_keras_command = f"python ../../bin/convert_keras.py {keras_model_path} --input_shape "(1,224,224,3)" --out {args.out}"
    if args.encoding:

After Change

    graph = KerasConverter(batch_size=1).convert(model)
    for backend in ["webgpu", "webassembly", "fallback"]:
        graph_exec_data = generate_descriptor(backend, graph, constant_encoder_name=args.encoding)
        graph_exec_data.save(args.out)

    console.stderr("Done.")

Instances