import tensorflow as tf

    N_ch -- number of channels, if any  (for the feature vector only)

    Returns:
    one_hot -- one hot matrix encoding
    """

    # Create a tensot flow constant equal to the number of classes
    C = tf.constant(N_classes, name="C")
    one_hot_matrix = tf.one_hot(vect-1, C, axis=0) #axis=0 means it is mapping to column vectors

    if N_ch != 0:
        one_hot_matrix= tf.expand_dims(one_hot_matrix, 1)

    # Create tensodr flow session
    sess = tf.Session()

