在 NodeJS 上运行 Frozen Tensorflow 模型

Question

I'm new to tensorflowjs (and js in general), however I need to run a trained model on it. Currently I converted the model to json format, but struggle to feed data to it:

const tf = require('@tensorflow/tfjs')
const tfn = require('@tensorflow/tfjs-node-gpu')

async function start() { 
    const handler = tfn.io.fileSystem("./model/model.json"); 
    const model = await tf.loadGraphModel(handler); 
    let latents = tf.randomNormal([1,512], 'float32'); 
    let labels = tf.zeros([1, 0]); 
    model.predict([latents, labels]);
}
start();

But I receive an error saying The Conv2D op currently supports NHWC tensor format on the CPU. The op was given the format: NCHW The Conv2D op currently supports NHWC tensor format on the CPU. The op was given the format: NCHW

So as I understood, it is a tfjs issue, so I tried to create a float32 array and pass it to model like this:

var f32array = new Float32Array(512);
model.predict([f32array, labels]);

But then I see an error saying the dtype of dict['Gs/latents_in'] provided in model.execute(dict) must be float32, but was undefined

With python, I'm running inference by using this code:

graph = load_graph("dash/frozen_model.pb")

    x = graph.get_tensor_by_name('prefix/Gs/latents_in:0')
    x2 = graph.get_tensor_by_name('prefix/Gs/labels_in:0')
    y = graph.get_tensor_by_name('prefix/Gs/images_out:0')


    with tf.Session(graph=graph, config = config) as sess:
        while True:
            start_time = time.time()

            latents = np.random.randn(1, 512).astype(np.float32)
            labels = np.zeros([latents.shape[0], 0], np.float32)
            y_out = sess.run(y, feed_dict = { x: latents, x2: labels})

Would appreciate any help

Answer 1

Passing the data as Float32Array will not work since model.predict expects either a tensor or an array of tensors.

As indicated by the error:

The Conv2D op currently supports NHWC tensor format on the CPU. The op was given the format: NCHW

the conv2D as of the version 1.6 in js only supports the format NHWC. The only thing you can do is to change the model in python in order to use only the NHWC format.