I'm trying to load a model I develop in tensorflow (Python) with tensorflowjs and make prediction for an input test, as follow: tf_model = await tf.loadGraphModel('http://localhost:8080/tf_models/models_js/model/model.json') let test_output = await tf_model.predict(tf.tensor2d([0.0, -1.0, 1.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0], [1, 9], 'float32')) console.log("[Test tf model]:", test_output.arraySync()) I'm getting this error in the js console at tf_model.predict Error: Argument 'x' passed to 'conv2d' must be float32 tensor, but got int32 tensor even if the input of the Conv2D Layer is of type float32 in the model definition inputs = tf.keras.layers.Input((9)) # One-Hot encoding x = tf.cast(tf.one_hot(tf.cast(inputs + 1, tf.int32), 3), tf.float32) x = tf.reshape(x, (-1, 3, 3, 3)) x = tf.keras.layers.Conv2D( filters=3**5, kernel_size=(3, 3), kernel_regularizer=kernel_regularizer )(x) Anybody knows why this could happen?...