[ML][Pipeline] Implement CustomFilter callback

[ML][Pipeline] Implement CustomFilter callback

ACR: TWDAPI-274

This is the second part of CustomFilter implementation. It adds
transfering the data between JS and C++.

[Verification] Code tested with the snippets below works fine

// Valid CustomFilter callback - the happy scenario
var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");
    var outputTD = outputTI.getTensorsData();
    var rawInputData = input.getTensorRawData(0);
    for (var i = 0; i < rawInputData.data.size; ++i) {
        rawInputData.data[i] = rawInputData.data[i] + 1;
    }
        outputTD.setTensorRawData(0, rawInputData.data);
        return new tizen.ml.CustomFilterOutput(0, outputTD);
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called
// PAUSED

pipeline.start()

// PLAYING
// <CustomFilter and SinkListener callbacks' outputs 3 times>

////////////////////////////////////////////////////////////

// Valid CustomFilter callback - the happy scenario; ignore the data

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");
        return new tizen.ml.CustomFilterOutput(1, null); // ignore data
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called
// Custom filter called
// Custom filter called
// PAUSED

pipeline.start()

// PLAYING

////////////////////////////////////////////////////////////

// Valid CustomFilter callback - CustomFilter returns an error

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");
        return new tizen.ml.CustomFilterOutput(-1, null);
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called
// PAUSED

pipeline.start()

// PLAYING

////////////////////////////////////////////////////////////

// Invalid CustomFilter callback output - status == 0, but no
TensorsData

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");

    return new tizen.ml.CustomFilterOutput(0, null);
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called
// custom filter error:
// {name: "AbortError", message: "CustomFilter has thrown exception:
// {'code':0, 'name':'InvalidValuesError' ..."}

////////////////////////////////////////////////////////////

// Invalid CustomFilter callback output - non-CustomFilterOutput

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");

    return 123;
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called
// custom filter error:
// {name: "TypeMismatchError",
// message: "The value returned from CustomFilter is not a
// CustomFilterOutput object"}

////////////////////////////////////////////////////////////
// CustomFilter callback returns TensorsData with dimensions other
// than specified in tizen.ml.pipeline.registerCustomFilter(...) call

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");

    var invalidOutputTI = new tizen.ml.TensorsInfo();
    invalidOutputTI.addTensorInfo('ti1', 'UINT8', [5, 2]);

    var outputTD = invalidOutputTI.getTensorsData();

    outputTD.setTensorRawData(0, [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]);
    return new tizen.ml.CustomFilterOutput(0, outputTD);
}

// register - the happy scenario
tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called

// custom filter error: {name: "InvalidValuesError",
// message: "Output's TensorsInfo is not equal to expected"}

pipeline.start()

////////////////////////////////////////////////////////////

// CustomFilter callback returns non-TensorsData as output

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var flattenPlusOne = function(input) {
    console.log("Custom filter called");

    return new tizen.ml.CustomFilterOutput(0, "this should be TensorsData");
}

// register - the happy scenario
tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenPlusOne, inputTI,
    outputTI, function errorCallback(error) {
        console.warn('custom filter error:') ; console.warn(error);
    });

var pipeline_def = "videotestsrc num-buffers=3 "
                   + "! video/x-raw,width=20,height=15,format=BGRA "
                   + "! tensor_converter "
                   + "! tensor_filter framework=custom-easy model=testfilter2 "
                   + "! appsink name=mysink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})

pipeline.registerSinkListener('mysink', function(sinkName, data) {
    console.log('SinkListener for "' + sinkName + '" sink called');
    console.log(data);
})

// READY
// Custom filter called
// custom filter error:
// {name: "AbortError", message: "CustomFilter has thrown exception: {
..."}

////////////////////////////////////////////////////////////

// Invalid CustomFilterOutput.status

new tizen.ml.CustomFilterOutput(666, null);
// InvalidValuesError,
//  message: "CustomFilterOutput.status === 1 is the only legal positive value"

Change-Id: Icf2edee853eb97dde54ecd83f00164b302aa29ca
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>