

def dropout(x, level, seed=None):
    'Sets entries in `x` to zero at random,\n    while scaling the entire tensor.\n\n    # Arguments\n        x: tensor\n        level: fraction of the entries in the tensor\n            that will be set to 0\n        seed: random seed to ensure determinism.\n    '
    retain_prob = (1.0 - level)
    if (seed is None):
        seed = np.random.randint(10000000.0)
    return tf.nn.dropout((x * 1.0), retain_prob, seed=seed)

dataset/ETHPy150Open fchollet/keras/keras/backend/tensorflow_backend.py dropout/original