First off, we are going to define the model inputs function, which will create the model input placeholders to be used for feeding data to the computational model:

# defining the model inputs
def inputs(actual_dim, z_dim):
    inputs_actual = tf.placeholder(tf.float32, (None, *actual_dim), name='input_actual')
    inputs_latent_z = tf.placeholder(tf.float32, (None, z_dim), name='input_latent_z')

    target = tf.placeholder(tf.int32, (None), name='target')
    label_mask = tf.placeholder(tf.int32, (None), name='label_mask')

    return inputs_actual, inputs_latent_z, target, label_mask