534a56bb2f790e17160586ed8a72b88d37de9c5a,autokeras/layer_transformer.py,,deeper_conv_block,#Any#Any#Any#,10

Before Change

                   np.ones(n_filters, dtype=np.float32)]
    new_conv_layer.set_weights([bn_weights, conv_weights])

    return new_conv_layer


def dense_to_deeper_block(dense_layer, weighted=True):
    Get deeper layer for dense layer

After Change

        weight[..., i] = filter_weight
    bias = np.zeros(n_filters)
    new_conv_layer = StubConv(n_filters, kernel_size=filter_shape, func=conv_layer.func)
    bn = StubBatchNormalization()

    if weighted:
        new_conv_layer.set_weights((add_noise(weight, np.array([0, 1])), add_noise(bias, np.array([0, 1]))))
        new_weights = [np.ones(n_filters, dtype=np.float32),
                       np.zeros(n_filters, dtype=np.float32),
                       np.zeros(n_filters, dtype=np.float32),
                       np.ones(n_filters, dtype=np.float32)]
        bn.set_weights(new_weights)

    return [bn,
            StubActivation("relu"),
            new_conv_layer,
            StubDropout(constant.CONV_DROPOUT_RATE)]


def dense_to_deeper_block(dense_layer, weighted=True):
    Get deeper layer for dense layer

Instances