Beispiel #1
0
def main():
    controller_start = time.time()
    SOS = SSOS()
    SOS.init()

    sos_host = "localhost"
    sos_port = os.environ.get("SOS_CMD_PORT")

    step = 0
    prior_frame_max = 0

    log(1, "Online.")
    print("CREATE VIEW", flush=True)  # ggout
    query.createApolloView(SOS, sos_host, sos_port)

    #log(1, "Wiping all prior data in the SOS database...")
    print("WIPE DATA", flush=True)  # ggout
    query.wipeAllExistingData(SOS, sos_host, sos_port)
    prev_dtree_def = None

    triggers = 0
    while (os.environ.get("SOS_SHUTDOWN") != "TRUE"):
        # Clearing prior training data
        # query.wipeTrainingData(SOS, sos_host, sos_port, prior_frame_max)
        prior_frame_max = query.waitForMoreRowsUsingSQL(
            SOS, sos_host, sos_port, prior_frame_max)
        data, region_names = query.getTrainingData(SOS,
                                                   sos_host,
                                                   sos_port,
                                                   row_limit=0)
        #print('data', data)
        #print('region_names', region_names)
        dataset_guid = SOS.get_guid()
        data.to_pickle("./output/models/step.%d.trainingdata.pickle" %
                       prior_frame_max)
        with open(
            ("./output/models/step.%d.region_names.pickle" % prior_frame_max),
                "wb") as f:
            pickle.dump(region_names, f)
        print("Pickled step ", prior_frame_max)  # ggout
        continue
        # ggout

        # Model: DecisionTree
        dtree_def, dtree_skl = trees.generateDecisionTree(
            log,
            data,
            assign_guid=dataset_guid,
            tree_max_depth=3,
            one_big_tree=False)
        dtree_len = len(dtree_def)

        if (dtree_len < 1):
            log(0, "No models generated for step %d." % prior_frame_max)
        else:
            with open(("./output/models/step.%d.model.json" % prior_frame_max),
                      "w") as f:
                f.write(dtree_def)

        if True:  #prev_dtree_def == None or prev_dtree_def != dtree_def:
            prev_dtree_def = dtree_def
            #SOS.trigger("APOLLO_MODELS", dtree_len, dtree_def)
            triggers += 1
            print("===> Trigger ",
                  triggers,
                  " because models differ",
                  flush=True)  # ggout

        # Model: RegressionTree
        #rtree_skl = trees.generateRegressionTree(log, data,
        #        assign_guid=dataset_guid,
        #        tree_max_depth=3,
        #        one_big_tree=False)

        # TODO(chad): Add NN models / streaming models here

        # TODO(chad): Drop models into an arena to fight, and only send models
        #             out when they are better than some prior model for any
        #             given loop. Could use async queues for analysis and for
        #             model distribution.

        if dtree_len > 0:
            if (ONCE_THEN_EXIT):
                controller_elapsed = time.time() - controller_start
                log(
                    1, "Done.  Full cycle of controller took " +
                    str(controller_elapsed) + "seconds.")
                return
        else:
            if (VERBOSE):
                log(1, "NOTICE: Model was not generated, nothing to send.")
            if (ONCE_THEN_EXIT):
                log(1, "Done.")
                return

        step += 1
        ##### return to top of loop until shut down #####

    ########## end of controller.py  ##########
    log(1, "Done.")
    return
Beispiel #2
0
def main():
    controller_start = time.time()
    SOS = SSOS()
    SOS.init()

    sos_host = "localhost"
    sos_port = os.environ.get("SOS_CMD_PORT")

    step = 0
    prior_frame_max = 0

    log(1, "Online.")
    query.createApolloView(SOS, sos_host, sos_port)

    #log(1, "Wiping all prior data in the SOS database...")
    #query.wipeAllExistingData(SOS, sos_host, sos_port)

    data = {}

    while (os.environ.get("SOS_SHUTDOWN") != "TRUE"):
        # Clearing prior training data from SOS
        # query.wipeTrainingData(SOS, sos_host, sos_port, prior_frame_max)
        data['prior_frame_max'] = \
                query.waitForMoreRowsUsingSQL(SOS, sos_host, sos_port, prior_frame_max)
        data['latest_query_rows'], data['latest_region_names'] = \
                query.getTrainingData(SOS, sos_host, sos_port, row_limit=0)

        pickle_latest_data(cargo)
        dataset_guid = SOS.get_guid()

        # Model: RegressionTree
        data['rtree_skl'] = trees.generateRegressionTree(
            log,
            data,
            assign_guid=dataset_guid,
            tree_max_depth=3,
            one_big_tree=False)

        # Model: DecisionTree
        data['dtree_def'], data['dtree_skl'] = \
                trees.generateDecisionTree(
                        log, data, assign_guid=dataset_guid,
                        tree_max_depth=3, one_big_tree=False)

        # TODO(chad): Bootstrap conditions VS. active monitoring conditions

        # Analyze the data coming in compared to existing rtree
        data['model_pkg_json'] = guide.analyzePerformance(data)

        # TODO(chad): Ship out the model package.

        if (ONCE_THEN_EXIT):
            controller_elapsed = time.time() - controller_start
            log(1, "Done.  Full cycle of controller took " \
                    + str(controller_elapsed) + "seconds.")
            return

        step += 1
        ##### return to top of loop until shut down #####

    ########## end of controller.py  ##########
    log(1, "Done.")
    return