'Initialization in the style of Glorot 2010.
stddev_factor should be 1.0 for linear activations, and 2.0 for ReLUs'

def _glorot_initializer(self, prev_units, num_units, stddev_factor=1.0):

    stddev = np.sqrt((stddev_factor / np.sqrt((prev_units * num_units))))
    return tf.truncated_normal([prev_units, num_units], mean=0.0, stddev=stddev)
