L1Decay

paddle.fluid.regularizer.L1Decay(regularization_coeff=0.0)

L1Decay实现L1权重衰减正则化,用于模型训练,使得权重矩阵稀疏。

具体实现中,L1权重衰减正则化的计算公式如下:

\[\begin{split}\\L1WeightDecay=reg\_coeff∗sign(parameter)\\\end{split}\]
参数:
  • regularization_coeff (float) – L1正则化系数,默认值为0.0。

代码示例

import paddle.fluid as fluid

main_prog = fluid.Program()
startup_prog = fluid.Program()
with fluid.program_guard(main_prog, startup_prog):
    data = fluid.layers.data(name='image', shape=[3, 28, 28], dtype='float32')
    label = fluid.layers.data(name='label', shape=[1], dtype='int64')
    hidden = fluid.layers.fc(input=data, size=128, act='relu')
    prediction = fluid.layers.fc(input=hidden, size=10, act='softmax')
    loss = fluid.layers.cross_entropy(input=prediction, label=label)
    avg_loss = fluid.layers.mean(loss)
optimizer = fluid.optimizer.Adagrad(
    learning_rate=1e-4,
    regularization=fluid.regularizer.L1Decay(
        regularization_coeff=0.1))
optimizer.minimize(avg_loss)