本文整理汇总了Python中classifier.Classifier.initialize方法的典型用法代码示例。如果您正苦于以下问题：Python Classifier.initialize方法的具体用法？Python Classifier.initialize怎么用？Python Classifier.initialize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classifier.Classifier的用法示例。
在下文中一共展示了Classifier.initialize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: build_model_mnist
# 需要导入模块: from classifier import Classifier [as 别名]
# 或者: from classifier.Classifier import initialize [as 别名]
def build_model_mnist():
# CNN
filter_size = (5, 5)
activation = Rectifier().apply
pooling_size = (2, 2)
num_filters = 50
layer0 = ConvolutionalLayer(activation=activation, filter_size=filter_size, num_filters=num_filters,
pooling_size=pooling_size,
weights_init=Uniform(width=0.1),
biases_init=Uniform(width=0.01), name="layer_0")
filter_size = (3, 3)
activation = Rectifier().apply
num_filters = 20
layer1 = ConvolutionalLayer(activation=activation, filter_size=filter_size, num_filters=num_filters,
pooling_size=pooling_size,
weights_init=Uniform(width=0.1),
biases_init=Uniform(width=0.01), name="layer_1")
conv_layers = [layer0, layer1]
convnet = ConvolutionalSequence(conv_layers, num_channels= 1,
image_size=(28, 28))
convnet.initialize()
output_dim = np.prod(convnet.get_dim('output'))
mlp = MLP(activations=[Identity()], dims=[output_dim, 10],
weights_init=Uniform(width=0.1),
biases_init=Uniform(width=0.01), name="layer_2")
mlp.initialize()
classifier = Classifier(convnet, mlp)
classifier.initialize()
return classifier