Package hivemall.mix.client

Examples of hivemall.mix.client.MixClient

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            model = new SparseModel(initModelSize, useCovar);
        }
        if(mixConnectInfo != null) {
            model.configureClock();
            model = new SynchronizedModelWrapper(model);
            MixClient client = configureMixClient(mixConnectInfo, label, model);
            model.setUpdateHandler(client);
            this.mixClient = client;
        }
        assert (model != null);
        return model;
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        String jobId = (mixSessionName == null) ? MixClient.DUMMY_JOB_ID : mixSessionName;
        if(label != null) {
            jobId = jobId + '-' + label;
        }
        MixEventName event = useCovariance() ? MixEventName.argminKLD : MixEventName.average;
        MixClient client = new MixClient(event, jobId, connectURIs, ssl, mixThreshold, model);
        logger.info("Successfully configured mix client: " + connectURIs);
        return client;
    }
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        waitForState(server, ServerState.RUNNING);

        PredictionModel model = new DenseModel(16777216, false);
        model.configureClock();
        MixClient client = null;
        try {
            client = new MixClient(MixEventName.average, "testSimpleScenario", "localhost:" + port, false, 2, model);
            model.setUpdateHandler(client);

            final Random rand = new Random(43);
            for(int i = 0; i < 100000; i++) {
                Integer feature = Integer.valueOf(rand.nextInt(100));
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        waitForState(server, ServerState.RUNNING);

        PredictionModel model = new DenseModel(16777216, false);
        model.configureClock();
        MixClient client = null;
        try {
            client = new MixClient(MixEventName.average, "testSSL", "localhost:" + port, true, 2, model);
            model.setUpdateHandler(client);

            final Random rand = new Random(43);
            for(int i = 0; i < 100000; i++) {
                Integer feature = Integer.valueOf(rand.nextInt(100));
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    }

    private static void invokeClient(String groupId, int serverPort) throws InterruptedException {
        PredictionModel model = new DenseModel(16777216, false);
        model.configureClock();
        MixClient client = null;
        try {
            client = new MixClient(MixEventName.average, groupId, "localhost:" + serverPort, false, 2, model);
            model.setUpdateHandler(client);

            final Random rand = new Random(43);
            for(int i = 0; i < 100000; i++) {
                Integer feature = Integer.valueOf(rand.nextInt(100));
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    private static void invokeClient01(String groupId, int serverPort, boolean denseModel)
            throws InterruptedException {
        PredictionModel model = denseModel ? new DenseModel(100, false)
                : new SparseModel(100, false);
        model.configureClock();
        MixClient client = null;
        try {
            client = new MixClient(MixEventName.average, groupId, "localhost:" + serverPort, false, 3, model);
            model.setUpdateHandler(client);

            final Random rand = new Random(43);
            for(int i = 0; i < 1000000; i++) {
                Integer feature = Integer.valueOf(rand.nextInt(100));
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Related Classes of hivemall.mix.client.MixClient

  • hivemall.LearnerBaseUDTF
  • hivemall.mix.MixMessage
  • hivemall.mix.NodeInfo
  • hivemall.mix.server.MixServerTest
  • io.netty.bootstrap.Bootstrap
  • io.netty.channel.Channel
  • io.netty.channel.ChannelFuture
  • io.netty.channel.EventLoopGroup
  • io.netty.channel.nio.NioEventLoopGroup
  • io.netty.handler.ssl.SslContext
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