b31f2cafe77bf3a2f738289a89438fb72936117c,autokeras/hypermodel/hyper_block.py,ConvBlock,build,#ConvBlock#Any#Any#,159

Before Change

                kernel_size,
                padding=self._get_padding(kernel_size, output_node))(output_node)

            output_node = tf.keras.layers.MaxPool2D(
                kernel_size - 1,
                padding=self._get_padding(kernel_size - 1, output_node))(output_node)
        return output_node

    @staticmethod
    def _get_padding(kernel_size, output_node):

After Change

        dropout_rate = hp.Choice("dropout_rate", [0, 0.25, 0.5], default=0.5)

        for i in range(hp.Choice("num_blocks", [1, 2, 3], default=2)):
            if dropout_rate > 0:
                output_node = dropout(dropout_rate)(output_node)
            output_node = conv(
                hp.Choice("filters_{i}_1".format(i=i),
                          [16, 32, 64],
                          default=32),

Instances