4b83c1070cebd0d996ba2cc69779dcb66d5d0032,autokeras/generator.py,DefaultClassifierGenerator,generate,#DefaultClassifierGenerator#Any#Any#,51

Before Change

        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)
            output_tensor = conv(model_width, kernel_size=self._get_shape(3), padding="same")(output_tensor)

After Change

        model.layers.append(StubGlobalPooling(ave))
        model.layers.append(StubDense(self.n_classes, activation="softmax"))
        model.outputs = [len(model.layers)]
        for index, layer in enumerate(model.layers):
            layer.input = index
            layer.output = index + 1
        return Graph(model, False)


class RandomConvClassifierGenerator(ClassifierGenerator):

Instances