7f30b2403fadc4eaad48ceaf6154a626f477f8c8,autokeras/generator.py,DefaultClassifierGenerator,generate,#DefaultClassifierGenerator#Any#Any#,51

Before Change

        output_tensor = ave()(output_tensor)
        output_tensor = Dense(self.n_classes, activation="softmax")(output_tensor)
        return Model(inputs=input_tensor, outputs=output_tensor)


class RandomConvClassifierGenerator(ClassifierGenerator):
    A classifier generator that generates random convolutional neural networks.

After Change

        model.inputs = [0]
        model.layers.append(StubInput())
        for i in range(model_len):
            model.layers += [StubBatchNormalization(),
                             StubActivation("relu"),
                             StubConv(model_width, kernel_size=3, func=conv),
                             StubDropout(constant.CONV_DROPOUT_RATE)]
            if (i + 1) % pooling_len == 0 and i != model_len - 1:
                model.layers.append(StubPooling(func=pool))

        model.layers.append(StubGlobalPooling(ave))

Instances