ave = get_ave_layer_func(len(self._get_shape(3)))
pooling_len = int(model_len / 4)
output_tensor = input_tensor = Input(shape=self.input_shape)
for i in range(model_len):
output_tensor = BatchNormalization()(output_tensor)
output_tensor = Activation("relu")(output_tensor)
After Change
for index, layer in enumerate(model.layers):
layer.input = index
layer.output = index + 1
return Graph(model, False)
class RandomConvClassifierGenerator(ClassifierGenerator):
A classifier generator that generates random convolutional neural networks.