Hello,
I’m pretty new to TF and just started by working around this tutorial: “pose classification in keras” 1.
I am using my own dataset for training/testing and I adjusted the model config :
model.compile(

    optimizer='adam',

    loss='categorical_crossentropy',

    metrics=['accuracy']

)

# Add a checkpoint callback to store the checkpoint that has the highest

# validation accuracy.

checkpoint_path = "weights.best.hdf5"

checkpoint = keras.callbacks.ModelCheckpoint(checkpoint_path,

                             monitor='val_accuracy',

                             verbose=1,

                             save_best_only=True,

                             mode='max')

earlystopping = keras.callbacks.EarlyStopping(monitor='val_accuracy', 

                                              patience=20)

# Start training

history = model.fit(X_train, y_train,

                    epochs=200,

                    batch_size=16,

                    validation_data=(X_val, y_val),

                    callbacks=[checkpoint, earlystopping])

tfjs.converters.save_keras_model(model,'./path')

when importing the tfjs converted model with this command:
model = await tf.loadLayersModel('./path');
I get the following error :
Error: Unknown layer: SlicingOpLambda. This may be due to one of the following reasons:
1. The layer is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
2. The custom layer is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().

I’m not post processing or rescaling the layers. If you know what the issue might be and have any suggestions, I’ll much appreciate it.
Thanks,
Parvin