Converting a tensorflow model to DN.

[jordan44665]

I would like to convert this tensorflow model to a DN cfg file. I am a nubee and don't know where to start. Any pointers would be appreciated. I was thinking adding the DN version of the layers for GlobalAveragePooling2D, Dropout, Dense to the existing resnet50.cfg. Would that work?

Thanks.

    inputs = Input(shape=(HEIGHT, WIDTH, DEPTH), name='inputs')
    base_model = ResNet50(weights='imagenet', include_top=False, input_shape=(HEIGHT, WIDTH, DEPTH),
                          input_tensor=inputs)
    base_model.trainable = False

    x1 = base_model.output
    x1 = GlobalAveragePooling2D()(x1)
    x1 = Dropout(0.5)(x1)
    x1 = Dense(512, activation='relu')(x1)
    x1 = Dropout(0.5)(x1)
    x1 = Dense(NUM_CLASSES, activation='softmax')(x1)

    model = Model(inputs=[base_model.input], outputs=