bool VisualManagerPass::drawScene(VisualParams* vp)
{
if(!multiPassEnabled)
return false;
if(renderToScreen.getValue())
{
glViewport(0,0,passWidth,passHeight);
glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT );
glEnable(GL_DEPTH_BUFFER_BIT);
//render opaque meshes
vp->pass() = sofa::core::visual::VisualParams::Std;
VisualDrawVisitor act ( vp );
act.setTags(this->getTags());
act.execute ( getContext() );
//render transparent meshes
vp->pass() = sofa::core::visual::VisualParams::Transparent;
VisualDrawVisitor act2 ( vp );
act2.setTags(this->getTags());
act2.execute ( getContext() );
return true;
}
else
return false;
}
/*==============================================================================
* FUNCTION: RtlTest::testClone
* OVERVIEW: Test constructor from list of expressions; cloning of RTLs
*============================================================================*/
void RtlTest::testClone () {
Assign* a1 = new Assign(
Location::regOf(8),
new Binary(opPlus,
Location::regOf(9),
new Const(99)));
Assign* a2 = new Assign(new IntegerType(16),
new Location(opParam, new Const("x"), NULL),
new Location(opParam, new Const("y"), NULL));
std::list<Statement*> ls;
ls.push_back(a1);
ls.push_back(a2);
RTL* r = new RTL(0x1234, &ls);
RTL* r2 = r->clone();
std::ostringstream o1, o2;
r->print(o1);
delete r; // And r2 should still stand!
r2->print(o2);
delete r2;
std::string expected("00001234 0 *v* r8 := r9 + 99\n"
" 0 *j16* x := y\n");
std::string act1(o1.str());
std::string act2(o2.str());
CPPUNIT_ASSERT_EQUAL(expected, act1);
CPPUNIT_ASSERT_EQUAL(expected, act2);
}
void VisualManagerPass::preDrawScene(VisualParams* vp)
{
if(renderToScreen.getValue() || (!multiPassEnabled))
return;
//const VisualParams::Viewport& viewport = vp->viewport();
fbo->setSize(passWidth, passHeight);
fbo->start();
glViewport(0,0,passWidth,passHeight);
glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT );
glEnable(GL_DEPTH_BUFFER_BIT);
//render opaque meshes
vp->pass() = sofa::core::visual::VisualParams::Std;
VisualDrawVisitor act ( vp );
act.setTags(this->getTags());
act.execute ( getContext() );
//render transparent meshes
vp->pass() = sofa::core::visual::VisualParams::Transparent;
VisualDrawVisitor act2 ( vp );
act2.setTags(this->getTags());
act2.execute ( getContext() );
fbo->stop();
prerendered=true;
}
void BookmarksToolbar::customContextMenuRequested(const QPoint &pos)
{
Q_UNUSED(pos)
QMenu menu;
menu.addAction(tr("&Bookmark Current Page"), p_QupZilla, SLOT(bookmarkPage()));
menu.addAction(tr("Bookmark &All Tabs"), p_QupZilla, SLOT(bookmarkAllTabs()));
menu.addAction(qIconProvider->fromTheme("user-bookmarks"), tr("&Organize Bookmarks"), p_QupZilla, SLOT(showBookmarksManager()));
menu.addSeparator();
QAction act(tr("Show Most &Visited"), this);
act.setCheckable(true);
act.setChecked(m_bookmarksModel->isShowingMostVisited());
connect(&act, SIGNAL(triggered()), this, SLOT(showMostVisited()));
menu.addAction(&act);
QAction act2(tr("Show Only Icons"), this);
act2.setCheckable(true);
act2.setChecked(m_bookmarksModel->isShowingOnlyIconsInToolbar());
connect(&act2, SIGNAL(triggered()), this, SLOT(toggleShowOnlyIcons()));
menu.addAction(&act2);
menu.addSeparator();
menu.addAction(tr("&Hide Toolbar"), this, SLOT(hidePanel()));
//Prevent choosing first option with double rightclick
QPoint position = mapToGlobal(pos);
QPoint p(position.x(), position.y() + 1);
menu.exec(p);
}
void display()
{
switch(num)
{
case 1:act1();break;
case 2:act2();break;
}
}
void DefaultVisualManagerLoop::drawStep(sofa::core::visual::VisualParams* vparams)
{
if ( !gRoot ) return;
if (gRoot->visualManager.empty())
{
vparams->pass() = sofa::core::visual::VisualParams::Std;
VisualDrawVisitor act ( vparams );
act.setTags(this->getTags());
gRoot->execute ( &act );
vparams->pass() = sofa::core::visual::VisualParams::Transparent;
VisualDrawVisitor act2 ( vparams );
act2.setTags(this->getTags());
gRoot->execute ( &act2 );
}
else
{
Node::Sequence<core::visual::VisualManager>::iterator begin = gRoot->visualManager.begin(), end = gRoot->visualManager.end(), it;
for (it = begin; it != end; ++it)
(*it)->preDrawScene(vparams);
bool rendered = false; // true if a manager did the rendering
for (it = begin; it != end; ++it)
if ((*it)->drawScene(vparams))
{
rendered = true;
break;
}
if (!rendered) // do the rendering
{
vparams->pass() = sofa::core::visual::VisualParams::Std;
VisualDrawVisitor act ( vparams );
act.setTags(this->getTags());
gRoot->execute ( &act );
vparams->pass() = sofa::core::visual::VisualParams::Transparent;
VisualDrawVisitor act2 ( vparams );
act2.setTags(this->getTags());
gRoot->execute ( &act2 );
}
Node::Sequence<core::visual::VisualManager>::reverse_iterator rbegin = gRoot->visualManager.rbegin(), rend = gRoot->visualManager.rend(), rit;
for (rit = rbegin; rit != rend; ++rit)
(*rit)->postDrawScene(vparams);
}
}
int hpx_main()
{
{
tuple_type t(42, 3.14, "test");
worker1_action act1;
act1(hpx::find_here(), t);
worker1_ref_action act2;
act2(hpx::find_here(), t);
}
{
tuple_base_type t(42, 3.14, "test");
worker2_action act1;
act1(hpx::find_here(), t);
worker2_ref_action act2;
act2(hpx::find_here(), t);
}
return hpx::finalize();
}
int main( int argc, char** argv ) {
boost::cmt::thread* at = boost::cmt::thread::create( "actor_thread" );
boost::reflect::any_ptr<calculator> ap( boost::make_shared<calculator>() );
boost::cmt::actor<calculator> act( boost::make_shared<calculator>(), at );
boost::cmt::actor<calculator> act2(ap, at );
boost::cmt::thread* tt = boost::cmt::thread::create( "test_thread" );
tt->async<void>( boost::bind(test, act) ).wait();
tt->async<void>( boost::bind(test, act2) ).wait();
at->async<void>( boost::bind(test, act2) ).wait();
//test(act);
test(act2);
tt->quit();
at->quit();
return 0;
}
int main( int argc, char** argv ) {
mace::cmt::thread* at = mace::cmt::thread::create( "actor_thread" );
mace::stub::ptr<calculator> ap( std::make_shared<calculator>() );
mace::cmt::actor<calculator> act( std::make_shared<calculator>(), at );
mace::cmt::actor<calculator> act2(ap, at );
mace::cmt::thread* tt = mace::cmt::thread::create( "test_thread" );
tt->async( boost::bind(test, act) ).wait();
tt->async( boost::bind(test, act2) ).wait();
at->async( boost::bind(test, act2) ).wait();
//test(act);
test(act2);
mace::cmt::usleep(100000);
tt->quit();
at->quit();
return 0;
}
int main (int argc, char **argv) {
ImageDataset d;
d.loadImagesFromFile("train-images-idx3-ubyte");
d.loadLabelsFromFile("train-labels-idx1-ubyte");
std::shared_ptr<clneural::ActivationFunction> act(new clneural::SigmoidActivationFunction());
std::shared_ptr<clneural::ActivationFunction> act2(new clneural::LinearActivationFunction());
std::vector<std::list<unsigned int>> C1_connections(6, std::list<unsigned int>({0}));
clneural::ConvolutionalLayer::Dimension C1_input;
clneural::ConvolutionalLayer::Dimension C1_filter;
float training_speed = 0.7f;
C1_input.width = 32;
C1_input.height = 32;
C1_filter.width = 5;
C1_filter.height = 5;
std::shared_ptr<clneural::NeuralNetworkLayer> C1(new clneural::ConvolutionalLayer(C1_input, C1_filter, C1_connections, act, training_speed));
clneural::SubsamplingLayer::Dimension S2_input;
clneural::SubsamplingLayer::Dimension S2_filter;
S2_input.width = 28;
S2_input.height = 28;
S2_filter.width = 2;
S2_filter.height = 2;
std::shared_ptr<clneural::NeuralNetworkLayer> S2(new clneural::SubsamplingLayer(S2_input, S2_filter, 6, act2, training_speed));
std::vector<std::list<unsigned int>> C3_connections(16);
C3_connections[0] = std::list<unsigned int>({0,1,2});
C3_connections[1] = std::list<unsigned int>({1,2,3});
C3_connections[2] = std::list<unsigned int>({2,3,4});
C3_connections[3] = std::list<unsigned int>({3,4,5});
C3_connections[4] = std::list<unsigned int>({4,5,0});
C3_connections[5] = std::list<unsigned int>({5,0,1});
C3_connections[6] = std::list<unsigned int>({0,1,2,3});
C3_connections[7] = std::list<unsigned int>({1,2,3,4});
C3_connections[8] = std::list<unsigned int>({2,3,4,5});
C3_connections[9] = std::list<unsigned int>({3,4,5,0});
C3_connections[10] = std::list<unsigned int>({4,5,0,1});
C3_connections[11] = std::list<unsigned int>({5,0,1,2});
C3_connections[12] = std::list<unsigned int>({0,1,3,4});
C3_connections[13] = std::list<unsigned int>({1,2,4,5});
C3_connections[14] = std::list<unsigned int>({0,2,3,5});
C3_connections[15] = std::list<unsigned int>({0,1,2,3,4,5});
clneural::ConvolutionalLayer::Dimension C3_input;
clneural::ConvolutionalLayer::Dimension C3_filter;
C3_input.width = 14;
C3_input.height = 14;
C3_filter.width = 5;
C3_filter.height = 5;
std::shared_ptr<clneural::NeuralNetworkLayer> C3(new clneural::ConvolutionalLayer(C3_input, C3_filter, C3_connections, act, training_speed));
clneural::SubsamplingLayer::Dimension S4_input;
clneural::SubsamplingLayer::Dimension S4_filter;
S4_input.width = 10;
S4_input.height = 10;
S4_filter.width = 2;
S4_filter.height = 2;
std::shared_ptr<clneural::NeuralNetworkLayer> S4(new clneural::SubsamplingLayer(S4_input, S4_filter, 16, act2, training_speed));
std::shared_ptr<clneural::NeuralNetworkLayer> N1(new clneural::FullFeedforwardLayer(400, 84, act, training_speed));
std::shared_ptr<clneural::NeuralNetworkLayer> N2(new clneural::FullFeedforwardLayer(84, 10, act, training_speed));
clneural::NeuralNetwork n;
n.addLayer(C1);
n.addLayer(S2);
n.addLayer(C3);
n.addLayer(S4);
n.addLayer(N1);
n.addLayer(N2);
std::shared_ptr<OpenCLInterface> ocl = OpenCLInterface::getInstance();
ocl->initialize(CL_DEVICE_TYPE_CPU);
float dist = 0.0f;
for (unsigned int i = 0; i < 60000; i++) {
std::pair<std::vector<float>, uint8_t> trainelem = d.popRandomElementWithLabel();
std::vector<float> desired(10, 0.0f);
desired[trainelem.second] = 1.0f;
dist += n.trainNetwork(trainelem.first, desired);
std::vector<float> nout = n.getLastOutput();
if ((i % 1000) == 0) {
std::cout << "TIME: " << ((float) clock())/CLOCKS_PER_SEC << ", STEP:" << (i + 1) << ", MDIST: " << dist/1000.0f << ", OUT: (" << nout[0];
for (unsigned int j = 1; j < nout.size(); j++) std::cout << "," << nout[j];
std::cout << "), DESIRED: (" << desired[0];
for (unsigned int j = 1; j < desired.size(); j++) std::cout << "," << desired[j];
std::cout << ")" << std::endl;
dist = 0.0f;
}
}
n.saveToFile("conv_images1.net");
verifyNetwork(n);
return 0;
}
void do_scan(CHAR_DATA *ch, char *argument)
{
extern char *const dir_name[];
char arg1[MAX_INPUT_LENGTH], buf[MAX_INPUT_LENGTH];
ROOM_INDEX_DATA *scan_room;
EXIT_DATA *pExit;
sh_int door, depth, outlet;
argument = one_argument(argument, arg1);
if (IS_AFFECTED(ch,AFF_BLIND))
{
send_to_char("Maybe it would help if you could see?\n\r",ch);
return;
}
if (arg1[0] == '\0')
{
act2("$n looks all around.", ch, NULL, NULL, TO_ROOM, ACTION_MUST_SEE);
send_to_char("Looking around you see:\n\r", ch);
scan_list(ch->in_room, ch, 0, -1);
for (door=0;door<6;door++)
{
outlet = door;
if ( ( ch->alignment < 0 )
&& (pExit = ch ->in_room->exit[door+6]) != NULL)
outlet += 6;
if ((pExit = ch ->in_room->exit[outlet]) != NULL)
scan_list(pExit->u1.to_room, ch, 1, outlet);
}
return;
}
else if (!str_cmp(arg1, "n") || !str_cmp(arg1, "north")) door = 0;
else if (!str_cmp(arg1, "e") || !str_cmp(arg1, "east")) door = 1;
else if (!str_cmp(arg1, "s") || !str_cmp(arg1, "south")) door = 2;
else if (!str_cmp(arg1, "w") || !str_cmp(arg1, "west")) door = 3;
else if (!str_cmp(arg1, "u") || !str_cmp(arg1, "up" )) door = 4;
else if (!str_cmp(arg1, "d") || !str_cmp(arg1, "down")) door = 5;
else { send_to_char("Which way do you want to scan?\n\r", ch); return; }
act("You peer intently $T.", ch, NULL, dir_name[door], TO_CHAR);
act("$n peers intently $T.", ch, NULL, dir_name[door], TO_ROOM);
sprintf(buf, "Looking %s you see:\n\r", dir_name[door]);
scan_room = ch->in_room;
for (depth = 1; depth < 4; depth++)
{
outlet = door;
if (scan_room == NULL) return;
if ( ( ch->alignment < 0 )
&& ((pExit = scan_room->exit[outlet+6]) != NULL))
{
scan_room = pExit->u1.to_room;
scan_list(pExit->u1.to_room, ch, depth, outlet+6);
}
else if ((pExit = scan_room->exit[outlet]) != NULL)
{
scan_room = pExit->u1.to_room;
scan_list(pExit->u1.to_room, ch, depth, outlet);
}
}
return;
}
