本文整理汇总了Python中keras.models.Sequential.regularizers方法的典型用法代码示例。如果您正苦于以下问题：Python Sequential.regularizers方法的具体用法？Python Sequential.regularizers怎么用？Python Sequential.regularizers使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类keras.models.Sequential的用法示例。
在下文中一共展示了Sequential.regularizers方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: modeling
# 需要导入模块: from keras.models import Sequential [as 别名]
# 或者: from keras.models.Sequential import regularizers [as 别名]
def modeling(self, l = [2121, 100, 50, 10, 1]):
"""
Generate a model with the give number of layers.
Previously, always a 5 layer model is generated.
Now it is changed to make adaptive number of layers.
If l = [2121, 1], it is linear regressoin method.
- l2_param is a self parameter rather than an input parameter.
"""
l2_param = self.l2_param
model = Sequential()
model.add(Dense( l[1], input_shape=(l[0],)))
model.regularizers = [l2(l2_param)]
for n_w_l in l[2:]:
model.add(Activation('relu'))
#model.add(Dropout(0.4))
# model.add(Dense( n_w_l, W_regularizer = l2(.01)))
model.add(Dense( n_w_l))
return model