[Common] Added caching custom virutal paths

This change is related to:
https://review.tizen.org/gerrit/#/c/platform/core/api/webapi-plugins/+/260943/

As in some scenarios (when new storage is mounted) webapi clears cache,
there is a need to restore custom virtual paths which are set with
setVirtualPath() method.

[Verification] Code compiles without errors.

Change-Id: I9dde4025526936e8988ff610f70894d4dbb00e60

[ML] Update NNFWType name of TRIx NPU Series

SRNPU is an unofficial name of TRIx NPU series.
Update the name with the official name.
Fortuately "SRNPU" was first introduced with Tizen 6.5 releases.

We have decided to expose the official name of these NPU series of
TRIV and TRIA series, which are exposed via a common NPU-Engine
low-level driver: "TRIx-Engine".

Note that in some commercial products with TRIx NPU series,
the low-level drivers might be not available to applications.
In such cases, high-level drivers (with less hardware control)
that wrap the low-level drivers will be provided (e.g., VD-AIFW).

[ACR] https://code.sec.samsung.net/jira/browse/TWDAPI-280

Change-Id: I7385749ec94981c3a89fe918d548d2fc582594bd
Signed-off-by: MyungJoo Ham <myungjoo.ham@samsung.com>

[common] Add the definition of a legacy messaging interface

This recent change that introduced new binary messaging interfaces,
replacing XW_MESSAGING_INTERFACE_1 with XW_MESSAGING_INTERFACE_2.
This chang broken the build of webapi-plugins-teec project, which depends
on the declaration of the legacy interface.
This commit fixes this problem, by adding the legacy interface back
to XW_Extension.h.

[Verification] webapi-plugins builds. webapi-plugins-teec builds,
when webapi-plugins built with this change is installed in GBS root.

Change-Id: Ia057a8e9ea9d51e06616a0ad16dc28b3ea342d8c

[version] 2.85

Change-Id: I2524f9fcf99cf55054f69bf6da38b3404ba2e98e

[ml][single] Implemented communication in ML API

[Verification] Performance increased in Chromium console.
TCT passrate - 100%
Change-Id: I7079ec1a690696dc4acc5d827920603e3a12e9ab

[extension] Binary messanger implementation added

[verification] Code compiles without errors.

Change-Id: If98eaf371ffbb47a2bf39978f9529307a9e9b06f

[ML][Single] Fix invokeAsync

invokeAsync implementation did not should copy the input TensorsData
object, as it was supposed to. This commit adds copying

[Verification] Tested with the snippet below several times - the outputs
of invoke and invokeAsync were always identical:

var tensorsData;
var model;

function errorCallback(error)
{
    console.log("Error during invokeAsync: " + error.message);
}

function isSameArray(a, b) {
    if(a.length != b.length) {
        return false;
    }
    for(var i=0 ; i<a.length ; i++) {
        if(a[i] != b[i]) {
            return false;
        }
    }
    return true;
}

function successCallback(tensorsDataOut)
{
    var asyncResult = tensorsDataOut.getTensorRawData(0).data;
    var syncResultTD = model.invoke(tensorsData);
    var syncResult = syncResultTD.getTensorRawData(0).data;

    if (isSameArray(syncResult, asyncResult)) {
        console.log('Sync and async versions of invoke returned the same output');
    } else {
        console.error('Outputs of sync and async invoke versions differ!');
    }
}

function run_test () {
    model = tizen.ml.single.openModel("wgt-package/models/mobilenet_v1_1.0_224_quant.tflite", null, null, "TENSORFLOW_LITE", "ANY");

    var tensorsInfo = new tizen.ml.TensorsInfo();
    tensorsInfo.addTensorInfo("tensor", "UINT8", [224, 224, 3]);
    tensorsData = tensorsInfo.getTensorsData();
    var randomData = Array.from({length: 224 * 224 * 3}, () => Math.floor(Math.random() * 255));
    var rgb = new Uint8Array(randomData);
    tensorsData.setTensorRawData(0, rgb);
    model.invokeAsync(tensorsData, successCallback, errorCallback);
};

Change-Id: Iff0d39ca6be9e1c5d2ff3c9f9fc3d061d49377c5

[Alarm] Don't raise an error when an alarm without TYPE is found

tizen.alarm.get() and tizen.alarm.getAll() used to fail when alarms
without "TYPE" property in related app_control existed.
This commit returns such alarms as JS Alarm objects.

[Verification] tct-alarm-tizen-tests (auto): 100 %

I've tested in Chrome DevTools debugger, that when an alarm without
"type" property comes to JS, a valid "Alarm" object is created
(I don't provide any test code snippet, because it required stopping
app in the debugger).

Change-Id: I4b5bcea75509f454bd17b787c080417849720f5a
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[version] 2.84

Change-Id: Iaeb9f2c1ce570ad109ea4a5c34a512b4a328442e

[Filesystem] Change setVirtualPath method to be not enumerable

Feature of setVirtualPath is needed for proper handling virtual paths
in thread service model - related change:
https://review.tizen.org/gerrit/gitweb?p=platform/core/api/webapi-plugins.git;a=commit;h=4870490975f9cbfa3eb16cc892f3593cb74b6668

[Verification] Code compiles without errors. Code was properly
formatted.
Checked in chrome console - setVirtualPath is not iterable, but still
accessible.

Change-Id: Ia3d2720cd1267d0a4d002538f319cfd993e83d4a

Support setVirtualPath for thread-model wrt-service

thread-model wrt-service runs all service application on worker
thread as daemon process.

For the virtual path resolving, it cannot get service application's
path. i.e. /home/owner/apps_rw/{service_app_pkgid}/data, becuase
wrt-service is org.tizen.chromium-efl package.

Thus, setting virtual path will be set by wrt-service framework
before each node worker thread started.
 - node worker has own V8 context

Change-Id: I8dd5e524584ebe71416c86c1e8648a2c4cfc4b94
Signed-off-by: DongHyun Song <dh81.song@samsung.com>

Support setVirtualPath for thread-model wrt-service

thread-model wrt-service runs all service application on worker
thread as daemon process.

For the virtual path resolving, it cannot get service application's
path. i.e. /home/owner/apps_rw/{service_app_pkgid}/data, becuase
wrt-service is org.tizen.chromium-efl package.

Thus, setting virtual path will be set by wrt-service framework
before each node worker thread started.
 - node worker has own V8 context

Change-Id: I8dd5e524584ebe71416c86c1e8648a2c4cfc4b94
Signed-off-by: DongHyun Song <dh81.song@samsung.com>

[Filesystem] Fixed Blob to Uint8Array conversion

Fix inspired by this answer: https://stackoverflow.com/a/63920556/11502478

[Verification] in Chrome console:
// assume having wav file on the device
input = tizen.filesystem.openFile("documents/sample1.wav", "r")
blob = input.readBlob()  /// Blob {size: 1073218, type: ""}

output = tizen.filesystem.openFile("documents/sample1_output.wav", "w")
output.writeBlob(blob)
output.close()

output_test = tizen.filesystem.openFile("documents/sample1_output.wav", "r")
blob_test = output_test.readBlob()  /// Blob {size: 1073218, type: ""}

console.log("Verification passed: " + (blob.size === blob_test.size))

input.close()
output_test.close()

TCT (filesystem, deprecated) passrate 100%

Change-Id: I5e4beea31d69430e9dbe44a7899cf675e779c7f8

[version] 2.83

Change-Id: Ie9ee7bcf4b480406921ec878717b5592dd0cc9a5

Merge "[ML][Single] Added InvokeAsync() implementation" into tizen

Merge "[Application] Enable system events listener" into tizen

[ML][Single] Added InvokeAsync() implementation

[ACR] https://code.sec.samsung.net/jira/browse/TWDAPI-278

[Verification] Code compiles without errors.
TCT passrate of existing APIs didn't change.

Checked in chrome console with below snippets:
// initialize test data
model = tizen.ml.single.openModel("documents/model.tflite");

var tensorsInfo = new tizen.ml.TensorsInfo();
tensorsInfo.addTensorInfo("tensor", "UINT8", [3, 224, 224]);
var tensorsData = tensorsInfo.getTensorsData();

var tensorsInfoInvalid = new tizen.ml.TensorsInfo();
tensorsInfoInvalid.addTensorInfo("tensor", "UINT8", [3, 125, 125]);
var tensorsDataInvalid = tensorsInfoInvalid.getTensorsData();

function errorCallback(error) {
  console.log(error);
}

function successCallback(tensorsDataOut) {
  console.log("Inference finished successfully");
  console.log(tensorsDataOut.getTensorRawData(0));
  tensorsDataOut.dispose();
}

// success
// test1
model.invokeAsync(tensorsData, successCallback, errorCallback);
// test2
model.invokeAsync(tensorsData, successCallback);

// errors
// test3
model.invokeAsync(tensorsData);  // TypeMismatchError - sync
// test4
model.invokeAsync(null, successCallback);  // TypeMismatchError - sync
//  test5
model.invokeAsync(tensorsDataInvalid, successCallback, errorCallback);  // AbortError - async
// test6
model.setTimeout(1)
model.invokeAsync(tensorsData, successCallback, errorCallback);  // TimeoutError - async

// clear tensorsData
tensorsData.dispose();
tensorsInfo.dispose();

// test7 - use of disposed tesnsorsData
model.invokeAsync(tensorsData, successCallback, errorCallback);  // AbortError - sync

// clear other data
tensorsDataInvalid.dispose();
tensorsInfoInvalid.dispose();
model.close();

Change-Id: I59900d7bab9a76939e27d68cb2bcd5434f446b3d

[version] 2.82

Change-Id: I851cb3ea68068d0ea2fa38ac5eac19ca0a5904c1

[ML] Add new HWType and NNFWType enums

[XWALK-2312]
[TWDAPI-277]

Tested also with code:
var HWType = ["ANY", "NPU_SLSI"];

var NNFWType = ["ANY", "NNTR_INF", "PYTORCH", "SRNPU", "VD_AIFW"];

HWType.forEach(hw => {
    NNFWType.forEach(nnfw => {
        console.log(nnfw + ", " + hw + ": " + tizen.ml.checkNNFWAvailability(nnfw, hw))
    });
});

[Verification] 100% passrate

Change-Id: I9257240d1596c2b017581997b488a01447385060
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[version] 2.81

Change-Id: I5225e6004d027167b720b9f1fcd1d213a9840769

[Filesystem] Use non-static worker instead of singleton TaskQueue

In filesystem webapi, TaskQueue is a singleton instance used by
multiple FilesystemInstance. With thread model web service
applications, there might be smack violation because each service
app (thread) try to use same worker.

This commit resolves problem by changing usage of singleton TaskQueue to
a member worker owned by FilesystemInstance.

Commit keeps two separated workers for better operation
performance:
- global_worker queues 'global' operations on fielsystem instance e.g.
opening files, rename, move etc.
- file_worker queues only file operation as reading
Above design prevents to block 'quick' global operations in case of
long-lasting file reading/writing operation in background.

[Verification] Code compiles without errors.
Filesystem TCT passrate 100%.

Change-Id: Idf0bd1915f67b64a65fcc1afc2e17d011bb5b918
Signed-off-by: DongHyun Song <dh81.song@samsung.com>
Signed-off-by: Piotr Kosko/Tizen API (PLT) /SRPOL/Engineer/Samsung Electronics <p.kosko@samsung.com>

[Tools] Force clang-format version to 3.9

Using version newer than 3.9 results in a lot of format changes.

As user may want to use newer clang-format version for different
projects, script has been changed to use clang-format-3.9 executable.

[Verification] No change in C++ formatting

Change-Id: I4f569644549db8104bb39efc6bc1eca23ac6bbd6
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

Merge "[Bluetooth] Fix Coverity issue" into tizen

Merge "[nfc] Fixing memory management for messages and records" into tizen

Merge "[ML][common] Fix a Coverity issue" into tizen

Merge "[mediacontroller] Fixing Coverity issues" into tizen

[Bluetooth] Fix Coverity issue

Coverity issue numbers:
1227417
1227505
1229055

[Verification] Code compiles

Change-Id: Ie05e4184cf200b69615b2e4ba92d3d5cb291d4d0
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[nfc] Fixing memory management for messages and records

Should fix Coverity issues:
* 1227523
* 1227594
* 1228259
* 1228588
* 1229210
* 1229523
* 1229587

[Verification] Code compiles without errors.

Change-Id: I07813a855ce2d335fe783956a7af6f340a314602

[mediacontroller] Fixing Coverity issues

Fixes: 1192721

Change-Id: I1bd564b935d35f0586e174869f7df10cd0cc705b

[ML][common] Fix a Coverity issue

Coverity issue numver: 1229783

This commit fixes a potential memory leak.

[Verification] The code compiles (it's hard to provoke the code to enter
the problematic branch, so the new code wasn't executed)

Change-Id: Id560ffdffc18ff6bbf2bc987e8e0ad6853b2cdb6

[ML] Remove unneccessary comments and already resolved TODOs

[Verification] Code compiles

Change-Id: I4ccd17dcee4cc1344c739d20492c93f94f08545e
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML][Pipeline] Prevent a crash in ~CustomFilter and unregister failures

This commit fixes a crash that used to follow the sequence below:
1. ~CustomFilter() is called, but native
ml_pipeline_custom_easy_filter_unregister()
fails to unregister the filter. CustomFilter is
removed, but a pointer to this object (now defunct)
is still kept in CustomFilter::valid_filters_ container.
2. LockRequestIdToJSResponseMutexIfFilterIsNotWaitingForJSResponses,
that iterates over valid_filters_ accesses the destroyed object
and thus crashes the app.

This commit also changes the order of destruction of Pipeline and
CustomFilter objects managed by Web API. Pipeline objects should
be destroyed first.

[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: I4c5b773203239321de5826b5e4908c50cd84b7d6
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

Merge "[Common][ML] Fixing SVACE issues and code formatting" into tizen

[Archive] Fixed Coverity issue

Issue id: 1218132

[Verification]
  Code compiles, TCT passrate 100%.
  Coverity showed no issues:
   https://analysishub.sec.samsung.net/service/analyses/418348

Change-Id: I5d28891a7b2c3b42237c661474ea88d00e028184

[ML][single] Change InvalidValues to TypeMismatch

In case when no arguments are provided, TypeMismatch should be thrown.

Verification: Tested in google chrome console.

Change-Id: Iab1f606c8a731c096dd93f5e38b0ec4c9b6beb6f
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[Common][ML] Fixing SVACE issues and code formatting

[SVACE] 1222586, 1222593

[Verification] Code compiles without errors.

Change-Id: Ibf34be9edb25f1b4e61e8480c9b6ad42262d42a4

Merge "[ML][single] Fix SingleShot.input attribute change" into tizen

[ML][single] Fix SingleShot.input attribute change

Changing input attribute should enable invoking model with different tensor.
User should not be able to modify or dispose input by direct call.
Change is only possible by replacing whole object.

Code:

var ti1 = new tizen.ml.TensorsInfo()
ti1.addTensorInfo("three", "FLOAT32", [1, 1, 1, 1])
var td1 = ti1.getTensorsData(0);
var ti3 = new tizen.ml.TensorsInfo()
ti3.addTensorInfo("three", "FLOAT32", [3, 1, 1, 1])
var td3 = ti3.getTensorsData(0);

var model = tizen.ml.single.openModel("documents/add.tflite", null, null, "ANY", "ANY", false)
model.invoke(td1)
model.input = ti3
model.invoke(td3)

[Verification] Tested in Google Chrome console

Change-Id: Iac17fd72d7e417d30bad983f6c349bd5e5ef05ed
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

Merge "[ML][Pipeline] Prevent deadlock in CustomFilter" into tizen

[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>

[ML][Pipeline] Remove InvalidValuesError from createPipeline

ACR: TWDAPI-274

This commit removes InvalidValuesError from the list of valid
tizen.ml.pipeline.createPipeline() exceptions, because we cannot
reliably detect, when a pipeline description is invalid.
Instead, AbortError with custom message, suggesting that the
description may be invalid, will be used.

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

// Invalid pipeline definition
var pipeline_def = "invalid";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                                state => {console.log(state);})
// WebAPIException {name: "AbortError", message: "Could not create pipeline:
// invalid pipeline description or an internal error"}

//////////////////////////////////////////////////////////////////////
// Valid pipeline definition

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);
})

// pipeline starts properly

Change-Id: If8d08160cb98b3acc34812f47b2741c2cce83cd8
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[version] 2.80

Change-Id: I70978ba74a8a100745631723bdccd66239b7224e

Merge "[ML][Pipeline] Fix issues reported by TCT team" into tizen

[ML][Pipeline] Fix issues reported by TCT team

Fixed problems:
- Pipeline::{getNodeInfo, getSwitch, getValve}: throw TypeMismatchError
when no argument is passed
- NodeInfo::setProperty: throw TypeMismatchError, instead of AbortError
when value type is other than expected
- Pipeline::unregisterSinkListener: throw InvalidValuesError when sink
has not been registered

[Verification] Code was tested with the snippets below and worked fine

///// checking problems with getNodeInfo, getSwitch, getValve,
///// and unregisterSinkListener
var pipelineDefinition = "videotestsrc name=vsrc is-live=true " +
                         "! videoconvert " +
                         "! videoscale name=vscale " +
                         "! video/x-raw,format=RGBx,width=224,height=224,framerate=60/1 " +
                         "! tensor_converter " +
                         "! valve name=valvex " +
                         "! input-selector name=is01 " +
                         "! tensor_sink name=sinkx";
var pipeline = tizen.ml.pipeline.createPipeline(pipelineDefinition);

pipeline.getNodeInfo();
// TypeMismatchError

pipeline.getSwitch();
// TypeMismatchError

pipeline.getValve();
// TypeMismatchError

pipeline.unregisterSinkListener('test')
// InvalidValuesError

///// checking problem with setProperty
pipelineDefinition = "videotestsrc name=vsrc is-live=true " +
                    "! videoconvert " +
                    "! videoscale name=vscale " +
                    "! video/x-raw,format=RGBx,width=224,height=224,framerate=60/1 " +
                    "! tensor_converter " +
                    "! valve name=valvex " +
                    "! input-selector name=is01 " +
                    "! tensor_sink name=sinkx";
pipeline = tizen.ml.pipeline.createPipeline(pipelineDefinition);
nodeInfo = pipeline.getNodeInfo("vsrc");
nodeInfo.setProperty("is-live", "DOUBLE", NaN);
// TypeMismatchError

Change-Id: I25438b037e0a2dd2f91f8d9b398cffcaf457386b
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML][Single] Fix issues that came out after TCT tests

- SingleShot.openModel should throw TypeError when no arguments provided

[Verification] Tested in chrome-dev console

Change-Id: I13b7946aa90f86ff4becccb9834b76d4f6bf6d22
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

Merge "[ML][Pipeline] Invalidate CustomFilter arguments after return" into tizen

[ML][Pipeline] Invalidate CustomFilter arguments after return

ACR: TWDAPI-274

This commit makes input and output of a JS CustomFilter act as if they
were disposed after the callback's return.

[Verification] Change was tested in Chrome DevTools with the snippets
below. It works fine.

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);

    console.log(input);

    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
// TensorsData {_id: 0, _tensorsInfo: TensorsInfo, _disposable: false}
// PAUSED

pipeline.start()

// CustomFilter is called 3 times

inputFromCustomFilter.getTensorRawData(0)
inputFromCustomFilter.tensorsInfo
outputFromCustomFilter.getTensorRawData(0)
outputFromCustomFilter.tensorsInfo
// The 4 lines above result in the following exception
// WebAPIException {name: "AbortError", message: "TensorsData is disposed"}
// as expected

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

var inputTI = new tizen.ml.TensorsInfo();
inputTI.addTensorInfo('ti1', 'UINT8', [4, 20, 15, 1]);
var inputTD = inputTI.getTensorsData()

inputTD.dispose()

inputTD.tensorsInfo
inputTD.getTensorRawData(0)
// The 2 lines above result in the following exception
// WebAPIException {name: "AbortError", message: "TensorsData is disposed"}
// as expected - the behavior of TensorsData.dispose() did not change

Change-Id: Ib6c6afc4bb09ad2ce04bb85650b79868e9923b7b
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML][Common] Fix issues that came out after TCT tests

- tizen.ml.single and tizen.ml.prototype should be not writable
- TensorsInfo.addTensorsInfo should return newly added tensors info id
- ValidateBufferForTensorsData issue

[Verification] Tested in chromium console

Change-Id: I9ba7e074c79ffc7acb4de32a87a42db6c5f22beb
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

Merge "[ML] Change InvalidValuesError to TypeMismatchError for no args" into tizen

Merge "[MediaController] Add guards to map of playlists' handles" into tizen

[ML] Change InvalidValuesError to TypeMismatchError for no args

When function is called without args, converter throws TypeError.
This commit unifies it.

code_format has been also applied.

[Verification] Builts successful, tested in chrome console

Change-Id: I032fd3f78e06b561ae472cdbbafe3bcf4092a6d9
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[MediaController] Add guards to map of playlists' handles

Previously only mc_server handle were guarded by mutexes.
Playlist also needs one.

[Verification] Tested on TM1, tct-mediacontroller pass 100% x 10, no issue occurred.

Change-Id: I155cc4f2dd87d4b1237537532105b7c251689279
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[ML][Pipeline][Single] Fix SVACE issues

This commit fixes the following issues reported on
analysishub.sec.samsung.net (WGIDs):
- 457566
- 457567
- 457568

[Verification] Code compiles. SVACE analysis after
applying the patch
(https://analysishub.sec.samsung.net/service/analyses/394936)
found no errors.

CustomFilter tested in Chrome DevTools with the
snippet 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 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>

Change-Id: Id1d35167532c3aeecbd3c73c3546b80e31e8f76c
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[Application] Enable system events listener

[ACR] https://code.sec.samsung.net/jira/browse/TWDAPI-276

[Verification] Code compiles without errors.
TCT passrate for application, appcontrol, capablity, deprecated - 100%

Checked some of native events from:
https://docs.tizen.org/application/native/guides/app-management/event/

var app = tizen.application.getCurrentApplication();
watchId =
        app.addEventListener({"name": "location_enable_state"}, function(event, data)
        {
          console.log("Event" + JSON.stringify(event) + " Data: " + JSON.stringify(data));
        });

var watchId =
        app.addEventListener({"appId": app.appInfo.id, "name": "custom_user_event"}, function(event, data)
        {
          console.log("Event" + JSON.stringify(event) + " Data: " + JSON.stringify(data));
          /* Do something. */
        });

after triggering associated event - listener seem to be called properly:
> app.broadcastEvent({'name': 'custom_user_event'}, {'test': 't'})
console-via-logger.js:173 Event{"appId":"Bwk0GVY1f3.BasicUI40","name":"custom_user_event"} Data: {"test":"t"}
> // ebable location on device
console-via-logger.js:173 Event{"name":"LOCATION_ENABLE_STATE"} Data: {"value":"disabled","type":"LOCATION_ENABLE_STATE"}

Change-Id: I73ae5b2b180c441db4f2da2eb84292b04b8e188f
Id: I65c83787c7d366fef918103be882370614034354

Merge "[SPEC][UT] Add conditions to unit test build and run" into tizen

[SPEC][UT] Add conditions to unit test build and run

Unit tests can be run inside GBS - by setting flag in spec file.

[Verification] Built successful with unified, profile mobile, profile wearable
               both with ut flags on and off.

Change-Id: I2a89562893182cf35cd41f8b396a19c4777fe580
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[systeminfo] Fix armv8l and texture_format on RPI

[TSDF-257]

- RPI4 has armv8l architecture, which was not supported by webapi.
- RPI4 does not support any opnegles texture_format

[Verification] TM1 6.5 systeminfo TCT 100% pass. Tested in chrome console on RPI4.

Change-Id: Ic479e2860250ebe15033a2cf8a53f827a2bd4bcd
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[version] 2.79

Change-Id: I10b8b53727146f2ef80b8e98f1fcb5365ffd3ae8

Merge "[ML][Pipeline] Change CustomFilter interface and implementation" into tizen

Merge "[ML][Single] Implemented setTimeout and close" into tizen

Merge "[GYP] Update build configuration for ML API" into tizen

[ML][Single] Implemented setTimeout and close

[ACR] https://code.sec.samsung.net/jira/browse/TWDAPI-273

[Verification] Code compiles. Verified in chrome console:

var m = tizen.ml.single.openModel("/opt/usr/home/owner/media/Documents/mobilenet_v1_1.0_224_quant.tflite")   // success
// timeout check
// check if invoke works 'normally'
var ti = new tizen.ml.TensorsInfo();
ti.addTensorInfo("tensor", "UINT8", [3, 224, 224])
var td = ti.getTensorsData();
var tdout = m.invoke(td)  // success

// check if timeout will change behaviour of invoke, while short timeout is set
m.setTimeout(5)    // success
var tdout = m.invoke(td)  // TimeoutError

// check empty arguments
m.setTimeout()     // InvalidValuesError

// close check
m.close()    // success
// Abort error: "SingleShot object was closed and using it is no longer possible."
// for following calls:
m.close()
m.input
m.output
m.invoke()
m.getValue()
m.setValue()
m.setTimeout()

Change-Id: I3ff7b899fc1527f62aea24387cadf4d0f0db3f05

[GYP] Update build configuration for ML API

Change-Id: Icb9f4993e8bbeae6e2c12bfca6689d279823d54e

[ML][Pipeline] Change CustomFilter interface and implementation

ACR: TWDAPI-274

CustomFilter API and implementation are changed to avoid
copying TensorsData.

Change-Id: Id48b774c86b65f5b45f3dd74733c006b6a729b8c
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>
[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 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: Id48b774c86b65f5b45f3dd74733c006b6a729b8c
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML][single] SingleShot.invoke implementation added

ACR: TWDAPI-273

Test code:
var ti1 = new tizen.ml.TensorsInfo()
ti1.addTensorInfo("three", "FLOAT32", [1, 1, 1, 1])
var td1 = ti1.getTensorsData(0);
td1.setTensorRawData(0, [1]);
var ti3 = new tizen.ml.TensorsInfo()
ti3.addTensorInfo("three", "FLOAT32", [3, 1, 1, 1])
var td3 = ti3.getTensorsData(0);
td3.setTensorRawData(0, [1, 2, 3]);
var ti5 = new tizen.ml.TensorsInfo()
ti5.addTensorInfo("three", "FLOAT32", [5, 1, 1, 1])
var td5 = ti5.getTensorsData(0);
td5.setTensorRawData(0, [1, 2, 3, 4, 5]);

// using model from nnstreamer API
var m = tizen.ml.single.openModel('documents/add.tflite', null, null, "ANY", "ANY")

m.invoke(td1) // ok
m.invoke(td3) // error
m.invoke(td5) // error

var m_dynamic = tizen.ml.single.openModel('documents/add.tflite', null, null, "ANY", "ANY", true)

m_dynamic.invoke(td1) // ok
m_dynamic.invoke(td3) // ok
m_dynamic.invoke(td5) // ok

[Verification] Built successful. Tested in Chrome Dev console.

Change-Id: I25218c122c57d6cb781181388f94a27ee0605ee8
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

Merge "[ML][Pipeline] Implement CustomFilter callback" into tizen

Merge "[ML][Pipeline] Implement {register, unregister}CustomFilter" into tizen

[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>

[ML][Pipeline] Implement {register, unregister}CustomFilter

ACR: TWDAPI-274

This is the first part of the implementation of nnstreamer's pipeline
CustomFilter Web API. It enables registering and unregistering
CustomFilters, but they don't process the data.

[Verification] Tested with the snippets below, works fine

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 with: ");
    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);
}

// 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);})
// READY
pipeline.start()

// unregister - the happy scenario
tizen.ml.pipeline.unregisterCustomFilter('testfilter2')

// overwrite a previously registered filter - that's ok

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

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

// unregister nonexistent filter
tizen.ml.pipeline.unregisterCustomFilter('nonexistentfilter')
// InvalidValuesError: ""nonexistentfilter" CustomFilter not found"

Change-Id: Ib01490e669376149eae654937131116f5ec1a4df
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

Check thread smack label for thread-based app model

Legacy web service app had been launched on a process but
new web service app is launched on a thread to save memory usage.
With the thread-based app model, the thread smack label needs to be checked
from the path |/proc/<tid>/attr/current|.

Also, checking thread smack label is compatible with process-based app model
because main thread utilizes same path of |/proc/<pid>/attr/current| as well.

Change-Id: Ib02237c926a2deedcd91451a36dd2a3d832cfb04
Signed-off-by: Youngsoo Choi <kenshin.choi@samsung.com>

Merge "[Mediakey] Conditional support for module" into tizen

[Mediakey] Conditional support for module

Tested in chrome and with TCT (capability & mediakey).
With feature disabled:
TCT:
  capability 100% pass
  mediakey - not exectued
Chrome:
  > tizen.mediakey === undefined
  true

With feature enabled:
TCT:
  capability 100% pass
  mediakey 100% pass
Chrome:
  > tizen.mediakey === undefined
  false
  > tizen.mediakey
  MediaKeyManager {}

Change-Id: I1b6a4654c0aabcb2e21defd0d05936d65115263f

Merge "[ML][Common] Minor fixes" into tizen

[ML] Fixed SVACE issue - not initialized size_in_bytes

[SVACE] Issue 456940

Change-Id: Icc31326b1768939ed82dbd5efde76c156c5f9be9

[ML][Common] Minor fixes

ACR: TWDAPI-273/TWDAPI-274

This commit adds 2 missing logs and replaces one variable name with a
proper one.

[Verification] Tested with below snippets, works as expected

// This snippets  triggers the added log:
var pipeline_def = "videotestsrc num-buffers=3 ! videoconvert"
                   + " ! tensor_converter ! tensor_sink name=sinkx";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                      function(state) {console.log(state);});
// READY
// PAUSED

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

pipeline.start()
// registered SinkListener is called 3 times

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

// This snippet no longer triggers the changed log:
var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var outputTD = outputTI.getTensorsData();

outputTD.dispose()

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

// This snippet triggers the exception which message is now correct:

var outputTI = new tizen.ml.TensorsInfo();
outputTI.addTensorInfo('ti1', 'UINT8', [1200]);
var outputTD = outputTI.getTensorsData();
outputTD.setTensorRawData(0, 'invalid data');

Change-Id: Iec192971882b094cc93679f2104499568dc43777
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

Merge "[ML-API] Use capi-ml-inference package instead of capi-nnstreamer" into tizen

[ML] Added SingleShot openModelAsync() implementation

[ACR] https://code.sec.samsung.net/jira/browse/TWDAPI-273

[Verification] Code compiles without errors.
Checked in chrome console with few calls:
// Success calls:
tizen.ml.single.openModelAsync("documents/mobilenet_v1_1.0_224_quant.tflite", (s) => console.log(s))
tizen.ml.single.openModelAsync("documents/mobilenet_v1_1.0_224_quant.tflite", (s) => console.log(s), null, null, null, "TENSORFLOW_LITE")
tizen.ml.single.openModelAsync("documents/mobilenet_v1_1.0_224_quant.tflite", (s) => console.log(s), null, null, null, "TENSORFLOW_LITE", "ANY", true)

// Fails for invalid or not-existing file:
tizen.ml.single.openModelAsync("documents/fail.tflite", (s) => console.log(s), (e) => console.log(e)) // Abort Error
tizen.ml.single.openModelAsync("documents/notexisting", (s) => console.log(s), (e) => console.log(e)) // NotFound
tizen.ml.single.openModelAsync("notexisting", (s) => console.log(s), (e) => console.log(e)) // NotFound

// ASYNC version verification //
// without storage privilege
tizen.ml.single.openModelAsync("notexistingfile", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // async NotFoundError
tizen.ml.single.openModelAsync("/dddd/notexistingfile", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // async NotFoundError
tizen.ml.single.openModelAsync("documents/notexistingfile", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // throws SecurityError
tizen.ml.single.openModelAsync("documents/mobilenet_v1_1.0_224_quant.tflite", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // throws SecurityError
// with storage privilege
tizen.ml.single.openModelAsync("notexistingfile", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // async NotFoundError
tizen.ml.single.openModelAsync("/dddd/notexistingfile", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // async NotFoundError
tizen.ml.single.openModelAsync("documents/notexistingfile", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // async NotFoundError
tizen.ml.single.openModelAsync("documents/mobilenet_v1_1.0_224_quant.tflite", (s) => console.log(s), (e) => console.log("Async: " + JSON.stringify(e)))   // success

// SYNC version verification //
// without storage privilege
tizen.ml.single.openModel("notexistingfile")   // throws NotFoundError
tizen.ml.single.openModel("/dddd/notexistingfile")   // throws NotFoundError
tizen.ml.single.openModel("documents/notexistingfile")   // throws SecurityError
tizen.ml.single.openModel("documents/mobilenet_v1_1.0_224_quant.tflite")   // throws SecurityError

// with storage privilege
tizen.ml.single.openModel("notexistingfile")   // throws NotFoundError
tizen.ml.single.openModel("/dddd/notexistingfile")   // throws NotFoundError
tizen.ml.single.openModel("documents/notexistingfile")   // throws NotFoundError
tizen.ml.single.openModel("documents/mobilenet_v1_1.0_224_quant.tflite")   // success

Change-Id: I93e009efec4e1bcbe6d6c3b381b34cada910d8aa

Merge "[ML][single] SingleShot.setValue and SingleShot.getValue" into tizen

[ML-API] Use capi-ml-inference package instead of capi-nnstreamer

The name of capi-nnstreamer and its pc file is changed to
capi-ml-inference. To build without any errors, this patch updates its
related information.

Change-Id: I037cc1151461fbaacfd87fcf2175e32b65dd337e
Signed-off-by: Sangjung Woo <sangjung.woo@samsung.com>

[ML][single] SingleShot.setValue and SingleShot.getValue

ACR: TWDAPI-273

Test code:
var m = tizen.ml.single.openModel('documents/mobilenet_v1_1.0_224_quant.tflite')
var arr = ["input", "inputtype", "inputlayout", "output", "outputtype", "outputlayout",
           "accelerator", "is-updatable", "inputname", "outputname", "custom" ]

arr.forEach((v) => {
    try {
        console.log(v, ':', m.getValue(v));
    } catch (error) {
        console.log(v, ':', error.message)
    }
});

m.setValue("input", "3:244:244:4");
console.log("input: " + m.getValue("input"))
m.setValue("is-updatable", "true");
console.log("is-updatable: " + m.getValue("is-updatable"))

[Verification] Built successful. Tested in Chrome Dev console.

Change-Id: Id911ed1717fb7b96c7ac75350ea27c78786cc5d9
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[ML][common] Add synchronization of access to tensor info/data maps

ACR: TWDAPI-273/TWDAPI-274

Pipeline's SinkCallbacks and CustomFilters may be called from threads
other than the main thread. As they access members of
Tensors{Data, Info}Managers, the access to these members should be
synchronized to prevent 2 threads from modifying the same data
concurrently.

[Verification] Tested with code snippets used from other commits
implementing Tensors{Data, Info} or Pipeline - the snippets still work.
The snippets used for tests were found in commit messages of these changes:
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/251435
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/251699
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/251524
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/252001
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/252002
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/252289
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/252290
https://review.tizen.org/gerrit/c/platform/core/api/webapi-plugins/+/252482

Change-Id: I32f5df4ba92e86034c78d751e901c77a9d60ca4e
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML][pipeline] Implement Pipeline::{register,unregister}SinkListener

ACR: TWDAPI-274

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

var pipeline_def = "videotestsrc num-buffers=3 ! videoconvert"
                   + " ! tensor_converter ! tensor_sink name=sinkx";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                      function(state) {console.log(state);});
// READY
// PAUSED

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

pipeline.start()
// registered SinkListener is called 3 times

Change-Id: I8790327d070e54d27fd9cc028882773487a48d7a
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

Merge "[ML][Common] Add unit tests to TensorsData::GetTensorRawData" into tizen

Merge "[ML][Common] Add TensorsData.getTensorRawData location/size support" into tizen

Merge "[ML][Common] Add unit tests to TensorsData::SetTensorRawData" into tizen

Merge "[ML][Common] Add TensorsData.setTensorRawData location/size support" into tizen

[ML][Common] Add unit tests to TensorsData::GetTensorRawData

[==========] 17 tests from 2 test suites ran. (120 ms total)
[  PASSED  ] 17 tests.

[Verification] Built successful. Tested on TM1

Change-Id: Ia73add4cab4500de078ce45933ca68f952975e4e
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[ML][Common] Add TensorsData.getTensorRawData location/size support

ACR: TWDAPI-273

Test code:
var ti = new tizen.ml.TensorsInfo();
ti.addTensorInfo("tensor", "INT16", [3, 3])
var td = ti.getTensorsData();
td.setTensorRawData(0, [1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 0], [3, 3])
var data = td.getTensorRawData(0, [1, 1], [])
console.log(data)
console.log(data.data)
// Int16Array(4) [5, 6, 8, 9]
// 5, 6
// 8, 9
data = td.getTensorRawData(0, [0, 0], [3, 1])
console.log(data)
console.log(data.data)
// Int16Array(3) [1, 2, 3]
// 1, 2, 3
data = td.getTensorRawData(0, [2, 0], [1, 2])
console.log(data)
console.log(data.data)
// Int16Array(2) [3, 6]
// 3
// 6
data = td.getTensorRawData(0, [], [1, 1])
console.log(data)
console.log(data.data)
// Int16Array(1) [1]
data = td.getTensorRawData(0, [0, 1], [-1,1])
console.log(data)
console.log(data.data)
// Int16Array(1) [3] (4, 5, 6)

[Verification] Built successful. Tested in Chrome Dev console.

Change-Id: Ife781390e8806309bc72963f43a5d001bcd2f5c2
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[ML] Fix issues found by SVACE

This commit fixes the following SVACE problems (WGIDs) in ML:
456856, 456857, 456858

[Verification] Code compiles. The changed code was tested with the
snippets below

// Source
var pipeline_input = tizen.ml.pipeline.createPipeline("appsrc name=srcx ! "
+ "other/tensor,dimension=(string)1:1:1:1,type=(string)int8,"
+"framerate=(fraction)0/1 ! tensor_sink name=sinkx")

var source_input = pipeline_input.getSource("srcx")

// Valve
var pipeline_def = "videotestsrc is-live=true ! videoconvert ! videoscale"
     + " ! video/x-raw,format=RGBx,width=16,height=16,framerate=10/1"
     + " ! tensor_converter ! valve name=valve1 ! fakesink";

var pipeline = tizen.ml.pipeline.createPipeline(pipeline_def,
                                      function(state) {console.log(state);});
// READY
// PAUSED

var v = pipeline.getValve('valve1')
// Valve {name: "valve1", _pipeline_id: 1}

// Switch
var pipeline_def = "videotestsrc is-live=true"
                   + " ! videoconvert"
                   + " ! tensor_converter"
                   + " ! output-selector name=outs outs.src_0"
                   + " ! tensor_sink name=sink0 async=false outs.src_1"
                   + " ! tensor_sink name=sink1 async=false"

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

pipeline.getSwitch('outs')
// Switch {name: "outs", type: "OUTPUT_SELECTOR", _pipeline_id: 3}

Change-Id: I9316f6a9f6f225aaa741e25458b53109f7c17c16
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML][Common] Add unit tests to TensorsData::SetTensorRawData

[==========] 10 tests from 1 test suite ran. (60 ms total)
[  PASSED  ] 10 tests.

[Verification] Built successful. Tested on TM1.

Change-Id: I1b89508d28973e3b4ed7ae4a39eee88fb8685fbe
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[ML][Common] Add TensorsData.setTensorRawData location/size support

ACR: TWDAPI-273

Test code:
var ti = new tizen.ml.TensorsInfo();
ti.addTensorInfo("tensor", "INT16", [3, 3])
var td = ti.getTensorsData();
console.log(td.getTensorRawData(0).data)
// Int16Array(9) [0, 0, 0, 0, 0, 0, 0, 0, 0]
// 0 0 0
// 0 0 0
// 0 0 0
td.setTensorRawData(0, [1, 2, 3], [0, 2], [3, 1])
console.log(td.getTensorRawData(0).data)
// Int16Array(9) [0, 0, 0, 0, 0, 0, 1, 2, 3]
// 0 0 0
// 0 0 0
// 1 2 3
td.setTensorRawData(0, [4, 5, 6], [2, 0], [1, 3])
console.log(td.getTensorRawData(0).data)
// Int16Array(9) [0, 0, 4, 0, 0, 5, 1, 2, 6]
// 0 0 4
// 0 0 5
// 1 2 6
td.setTensorRawData(0, [9], [1, 1], [1, 1])
console.log(td.getTensorRawData(0).data)
// Int16Array(9) [0, 0, 4, 0, 9, 5, 1, 2, 6]
// 0 0 4
// 0 9 5
// 1 2 6
td.setTensorRawData(0, [-4,3,-7], [0, 2], [-1, 1])
console.log(td.getTensorRawData(0).data)
// Int16Array(9) [0, 0, 4, 0, 9, 5, -4, 3, -7]
//  0  0  4
//  0  9  5
// -4  3 -7

[Verification] Built successful. Tested in Chrome Dev console.

Change-Id: Ibc4ae4ddef35941678a765acd5a300cefa6671b0
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[Notification] Fix SVACE issue

This commit fixes SVACE issue with WGID: 449860

[Verification] tct-notification-tizen-tests (auto): 100% pass rate
(The CommonNotification::SetAppControlInfoFrmJson function that was
changed, was called several times during tests)

Change-Id: If1caa5d141edb6c776a49ee9c2bfa5abc575efab

Merge "[ML][Pipeline] Input data" into tizen

[ML][Pipeline] Input data

ACR: TWDAPI-274

[Verification] Code compiles without error. Tested in chrome console.

var pipeline_input = tizen.ml.pipeline.createPipeline("appsrc name=srcx ! other/tensor,dimension=(string)1:1:1:1,type=(string)int8,framerate=(fraction)0/1 ! tensor_sink name=sinkx")

var source_input = pipeline_input.getSource("srcx")

var ti = new tizen.ml.TensorsInfo();
ti.addTensorInfo("tensor1", "UINT8", [1, 1])
var td = ti.getTensorsData();
console.log(td.count)

source_input.inputData(td)

tensor_input = source_input.inputTensorsInfo
td_input = tensor_input.getTensorsData()

tt = td_input.tensorsInfo
console.log(tt.getTensorName(0))

Change-Id: I4dd4c3cec5d77d36598551a5d3aa8d8a9fbc9b5a
Signed-off-by: Lukasz Bardeli <l.bardeli@samsung.com>

[ML][common] Add a method for cloning native tensors

ACR: TWDAPI-273/TWDAPI-274

This commit adds a method for cloning data and info from
ml_tensors_data_h and ml_tensors_info_h to TensorsData and related
TensorsInfo objects.

[Verification] Code compiles. Operation is verified in the next commit.

Change-Id: I0268e4d902b7f9a25b5ae531471cdf2028acd77b
Signed-off-by: Pawel Wasowski <p.wasowski2@samsung.com>

[ML] Fixed logger type with macro

For some architectures int64_t is not casted to lld, for partablitiy
stackoverflow suggests using macro.

[Verification] Code compiles for aarch64 architecture

Change-Id: I7aaa3dabeacae6ea7b212c09c5070ff011c64ab1

Merge "[systeminfo] Prevent possible crash when failure initialization" into tizen

[systeminfo] Prevent possible crash when failure initialization

SVACE: 456450

[verification] Code compiles without errors

Change-Id: I0b2f0c0c8d27ff0cc6edf3099f7ec77a2d825c7c

[ML][Common] Add TensorRawData and size/location validation on JS side

C++ validation will be added in future commit

Test code:
var ti = new tizen.ml.TensorsInfo();
ti.addTensorInfo("tensor1", "UINT8", [1, 1])
ti.addTensorInfo("tensor2", "INT16", [2, 4])
ti.addTensorInfo("tensor3", "FLOAT32", [2, 2])
var td = ti.getTensorsData();
console.log(td.getTensorRawData(0))
console.log(td.getTensorRawData(1))
console.log(td.getTensorRawData(2))

[Verification] Built successful. Tested in Chrome Dev console.

Change-Id: I14caa9a91b04ed2664cca241da54977a711b1abd
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>

[ML][Common] Add TensorsData.setTensorRawData method

ACR: TWDAPI-273

Test code:
var ti = new tizen.ml.TensorsInfo();
ti.addTensorInfo("tensor1", "UINT8", [1, 1])
var td = ti.getTensorsData();
console.log(td.getTensorRawData(0));
td.setTensorRawData(0, [13]);
console.log(td.getTensorRawData(0));

[Verification] Built successful. Tested in Chrome Dev console.

Change-Id: I522112df9a69f1a5ec7bbcbc12094296a11ec1c9
Signed-off-by: Rafal Walczyna <r.walczyna@samsung.com>