[ML][Pipeline] Prevent deadlock in CustomFilter

[ML][Pipeline] Prevent deadlock in CustomFilter

ACR: TWDAPI-274

A deadlock could happen in 2 scenarios:
1. An attempt of unregistering a CustomFilter from its callback, (i.e.
calling tizen.ml.pipeline.unregisterCustomFilter('xxx') from xxx's
CustomFilter callback).
2. An attempt of disposing the pipeline using a CustomFilter which is
currently processing data.
This commit fixes the problems.

[Verification] Tested in Chrome DevTools with the snippets below, works
fine.

inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo("3D", "UINT8", [4, 20, 15, 1]);
outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo("flat", "UINT8", [1200]);

filterCB = function (input, output) {
  console.log('hello');
  tizen.ml.pipeline.unregisterCustomFilter("flattenFilter");
  console.log('bye');
}

retValue = tizen.ml.pipeline.registerCustomFilter("flattenFilter", filterCB,
                                                  inputTI, outputTI,
                                                  console.warn);

pipelineDefinition = "videotestsrc num-buffers=3 " +
                    "! video/x-raw,width=20,height=15,format=BGRA " +
                    "! tensor_converter " +
                    "! tensor_filter framework=custom-easy model=flattenFilter "
                    + "! fakesink";
pipeline = tizen.ml.pipeline.createPipeline(pipelineDefinition);
pipeline.start();

// hello
// WebAPIException {name: "AbortError", message:
// "CustomFilter has thrown exception: InvalidStateErr CustomFilter has
// thrown exception: InvalidStateError: The custom filter is processing
// data now. Stop the pipeline to unregister the filter."}

// <no deadlock>

///////////////////////////////////////////////////////////////////////////
inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo("3D", "UINT8", [4, 20, 15, 1]);
outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo("ti1", "UINT8", [1200]);

customFilter = function (input, output) {
  try {
      inputTI.dispose();
      outputTI.dispose();
      pipeline.stop();
      pipeline.dispose();
  } catch (err) {
      console.warn(err);
  }
}

tizen.ml.pipeline.registerCustomFilter("flattenFilter", customFilter, inputTI, outputTI);

pipelineDefinition = "videotestsrc num-buffers=3 " +
                    "! video/x-raw,width=20,height=15,format=BGRA " +
                    "! tensor_converter " +
                    "! tensor_filter framework=custom-easy model=flattenFilter " +
                    "! fakesink";
pipeline = tizen.ml.pipeline.createPipeline(pipelineDefinition);
pipeline.start();

// WebAPIException {name: "InvalidStateError",
// message: "Pipeline cannot be disposed when at least one custom filter
// is currently processing data.",

// <no deadlock>

///////////////////////////////////////////////////////////////////////////
// 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 flattenAndSet123 = function(input, output) {
    console.log("Custom filter called");

    var rawOutputData = new Uint8Array(1200);
    for (var i = 0; i < rawOutputData.length; ++i) {
        rawOutputData[i] = 123;
    }

    output.setTensorRawData(0, rawOutputData);
    return 0;
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenAndSet123, 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, output) {
    console.log("Custom filter called");
        return 1; // 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, output) {
    console.log("Custom filter called");
        return -1;
}

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 CustomFilterOutput.status
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);
})

// InvalidValuesError,
//  message: "CustomFilterOutput.status === 1 is the only legal positive value"

////////////////////////////////////////////////////////////
// Check if {input, output}.dispose() and input.setTensorRawData()
// have any effect

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 flattenAndSet123 = function(input, output) {
    console.log("Custom filter called");

    // dispose should have no efect
    input.dispose();
    console.log('input count: ' + input.tensorsInfo.count);
    // dispose should have no efect
    input.dispose();
    console.log('output count: ' + output.tensorsInfo.count);

    var rawOutputData = new Uint8Array(1200);
    for (var i = 0; i < rawOutputData.length; ++i) {
        rawOutputData[i] = 123;
    }

    output.setTensorRawData(0, rawOutputData);

    // this call should have no effect
    input.setTensorRawData(0, rawOutputData);

    return 0;
}

tizen.ml.pipeline.registerCustomFilter('testfilter2', flattenAndSet123, 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);
})

Change-Id: Id6cda7782e3065248b2f2c5f859ca2af07c108a6
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>