def masking_noise(data, sess, v):
    """Apply masking noise to data in X.

    In other words a fraction v of elements of X
    (chosen at random) is forced to zero.
    :param data: array_like, Input data
    :param sess: TensorFlow session
    :param v: fraction of elements to distort, float
    :return: transformed data
    """
    data_noise = data.copy()
    rand = tf.random_uniform(data.shape)
    data_noise[sess.run(tf.nn.relu(tf.sign(v - rand))).astype(np.bool)] = 0

    return data_noise
Apply masking noise to data in X.

    In other words a fraction v of elements of X
    (chosen at random) is forced to zero.
    :param data: array_like, Input data
    :param sess: TensorFlow session
    :param v: fraction of elements to distort, float
    :return: transformed data
    
yadlt/utils/utilities.py