code
stringlengths 12
2.05k
| label_name
stringclasses 5
values | label
int64 0
4
|
|---|---|---|
QUInt8() {} | Base | 1 |
void CxImage::Startup(uint32_t imagetype)
{
//init pointers
pDib = pSelection = pAlpha = NULL;
ppLayers = ppFrames = NULL;
//init structures
memset(&head,0,sizeof(BITMAPINFOHEADER));
memset(&info,0,sizeof(CXIMAGEINFO));
//init default attributes
info.dwType = imagetype;
info.fQuality = 90.0f;
info.nAlphaMax = 255;
info.nBkgndIndex = -1;
info.bEnabled = true;
info.nJpegScale = 1;
SetXDPI(CXIMAGE_DEFAULT_DPI);
SetYDPI(CXIMAGE_DEFAULT_DPI);
int16_t test = 1;
info.bLittleEndianHost = (*((char *) &test) == 1);
}
| Base | 1 |
int jas_memdump(FILE *out, void *data, size_t len)
{
size_t i;
size_t j;
uchar *dp;
dp = data;
for (i = 0; i < len; i += 16) {
fprintf(out, "%04zx:", i);
for (j = 0; j < 16; ++j) {
if (i + j < len) {
fprintf(out, " %02x", dp[i + j]);
}
}
fprintf(out, "\n");
}
return 0;
} | Base | 1 |
int GetS32BE (int nPos, bool *pbSuccess)
{
//*pbSuccess = true;
if ( nPos < 0 || nPos + 3 >= m_nLen )
{
*pbSuccess = false;
return 0;
}
int nRes = m_sFile[ nPos ];
nRes = (nRes << 8) + m_sFile[nPos + 1];
nRes = (nRes << 8) + m_sFile[nPos + 2];
nRes = (nRes << 8) + m_sFile[nPos + 3];
if ( nRes & 0x80000000 )
nRes |= ~0xffffffff;
return nRes;
} | Base | 1 |
void BlockCodec::runPull()
{
AFframecount framesToRead = m_outChunk->frameCount;
AFframecount framesRead = 0;
assert(framesToRead % m_framesPerPacket == 0);
int blockCount = framesToRead / m_framesPerPacket;
// Read the compressed data.
ssize_t bytesRead = read(m_inChunk->buffer, m_bytesPerPacket * blockCount);
int blocksRead = bytesRead >= 0 ? bytesRead / m_bytesPerPacket : 0;
// Decompress into m_outChunk.
for (int i=0; i<blocksRead; i++)
{
decodeBlock(static_cast<const uint8_t *>(m_inChunk->buffer) + i * m_bytesPerPacket,
static_cast<int16_t *>(m_outChunk->buffer) + i * m_framesPerPacket * m_track->f.channelCount);
framesRead += m_framesPerPacket;
}
m_track->nextfframe += framesRead;
assert(tell() == m_track->fpos_next_frame);
if (framesRead < framesToRead)
reportReadError(framesRead, framesToRead);
m_outChunk->frameCount = framesRead;
} | Base | 1 |
RemoteFsDevice::RemoteFsDevice(MusicLibraryModel *m, const Details &d)
: FsDevice(m, d.name, createUdi(d.name))
, mountToken(0)
, currentMountStatus(false)
, details(d)
, proc(0)
, mounterIface(0)
, messageSent(false)
{
// details.path=Utils::fixPath(details.path);
setup();
icn=MonoIcon::icon(details.isLocalFile()
? FontAwesome::foldero
: constSshfsProtocol==details.url.scheme()
? FontAwesome::linux_os
: FontAwesome::windows, Utils::monoIconColor());
} | Base | 1 |
void AveragePool(const float* input_data, const Dims<4>& input_dims, int stride,
int pad_width, int pad_height, int filter_width,
int filter_height, float* output_data,
const Dims<4>& output_dims) {
AveragePool<Ac>(input_data, input_dims, stride, stride, pad_width, pad_height,
filter_width, filter_height, output_data, output_dims);
} | Base | 1 |
static int16_t decodeSample(ms_adpcm_state &state,
uint8_t code, const int16_t *coefficient)
{
int linearSample = (state.sample1 * coefficient[0] +
state.sample2 * coefficient[1]) >> 8;
linearSample += ((code & 0x08) ? (code - 0x10) : code) * state.delta;
linearSample = clamp(linearSample, MIN_INT16, MAX_INT16);
int delta = (state.delta * adaptationTable[code]) >> 8;
if (delta < 16)
delta = 16;
state.delta = delta;
state.sample2 = state.sample1;
state.sample1 = linearSample;
return static_cast<int16_t>(linearSample);
} | Base | 1 |
Variant HHVM_METHOD(XMLReader, expand,
const Variant& basenode /* = null */) {
auto* data = Native::data<XMLReader>(this_);
req::ptr<XMLDocumentData> doc;
xmlDocPtr docp = nullptr;
SYNC_VM_REGS_SCOPED();
if (!basenode.isNull()) {
auto dombasenode = Native::data<DOMNode>(basenode.toObject());
doc = dombasenode->doc();
docp = doc->docp();
if (docp == nullptr) {
raise_warning("Invalid State Error");
return false;
}
}
if (data->m_ptr) {
xmlNodePtr node = xmlTextReaderExpand(data->m_ptr);
if (node == nullptr) {
raise_warning("An Error Occurred while expanding");
return false;
} else {
xmlNodePtr nodec = xmlDocCopyNode(node, docp, 1);
if (nodec == nullptr) {
raise_notice("Cannot expand this node type");
return false;
} else {
return php_dom_create_object(nodec, doc);
}
}
}
raise_warning("Load Data before trying to read");
return false;
} | Base | 1 |
generatePreview (const char inFileName[],
float exposure,
int previewWidth,
int &previewHeight,
Array2D <PreviewRgba> &previewPixels)
{
//
// Read the input file
//
RgbaInputFile in (inFileName);
Box2i dw = in.dataWindow();
float a = in.pixelAspectRatio();
int w = dw.max.x - dw.min.x + 1;
int h = dw.max.y - dw.min.y + 1;
Array2D <Rgba> pixels (h, w);
in.setFrameBuffer (ComputeBasePointer (&pixels[0][0], dw), 1, w);
in.readPixels (dw.min.y, dw.max.y);
//
// Make a preview image
//
previewHeight = max (int (h / (w * a) * previewWidth + .5f), 1);
previewPixels.resizeErase (previewHeight, previewWidth);
float fx = (previewWidth > 0)? (float (w - 1) / (previewWidth - 1)): 1;
float fy = (previewHeight > 0)? (float (h - 1) / (previewHeight - 1)): 1;
float m = Math<float>::pow (2.f, IMATH_NAMESPACE::clamp (exposure + 2.47393f, -20.f, 20.f));
for (int y = 0; y < previewHeight; ++y)
{
for (int x = 0; x < previewWidth; ++x)
{
PreviewRgba &preview = previewPixels[y][x];
const Rgba &pixel = pixels[int (y * fy + .5f)][int (x * fx + .5f)];
preview.r = gamma (pixel.r, m);
preview.g = gamma (pixel.g, m);
preview.b = gamma (pixel.b, m);
preview.a = int (IMATH_NAMESPACE::clamp (pixel.a * 255.f, 0.f, 255.f) + .5f);
}
}
} | Base | 1 |
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
TfLiteType output_type = GetOutput(context, node, kOutputTensor)->type;
switch (output_type) { // Already know in/outtypes are same.
case kTfLiteFloat32:
EvalUnquantized<float>(context, node);
break;
case kTfLiteInt32:
EvalUnquantized<int32_t>(context, node);
break;
case kTfLiteUInt8:
EvalQuantizedUInt8(context, node);
break;
case kTfLiteInt8:
EvalUnquantized<int8_t>(context, node);
break;
case kTfLiteInt64:
EvalUnquantized<int64_t>(context, node);
break;
default:
TF_LITE_KERNEL_LOG(
context, "Op Concatenation does not currently support Type '%s'.",
TfLiteTypeGetName(output_type));
return kTfLiteError;
}
return kTfLiteOk;
} | Base | 1 |
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
TfLiteType output_type = GetOutput(context, node, kOutputTensor)->type;
switch (output_type) { // Already know in/outtypes are same.
case kTfLiteFloat32:
EvalUnquantized<float>(context, node);
break;
case kTfLiteInt32:
EvalUnquantized<int32_t>(context, node);
break;
case kTfLiteUInt8:
EvalQuantizedUInt8(context, node);
break;
case kTfLiteInt8:
EvalUnquantized<int8_t>(context, node);
break;
case kTfLiteInt64:
EvalUnquantized<int64_t>(context, node);
break;
default:
TF_LITE_KERNEL_LOG(
context, "Op Concatenation does not currently support Type '%s'.",
TfLiteTypeGetName(output_type));
return kTfLiteError;
}
return kTfLiteOk;
} | Base | 1 |
static jas_image_cmpt_t *jas_image_cmpt_create(int_fast32_t tlx,
int_fast32_t tly, int_fast32_t hstep, int_fast32_t vstep,
int_fast32_t width, int_fast32_t height, uint_fast16_t depth, bool sgnd,
uint_fast32_t inmem)
{
jas_image_cmpt_t *cmpt;
size_t size;
cmpt = 0;
if (width < 0 || height < 0 || hstep <= 0 || vstep <= 0) {
goto error;
}
if (!jas_safe_intfast32_add(tlx, width, 0) ||
!jas_safe_intfast32_add(tly, height, 0)) {
goto error;
}
if (!(cmpt = jas_malloc(sizeof(jas_image_cmpt_t)))) {
goto error;
}
cmpt->type_ = JAS_IMAGE_CT_UNKNOWN;
cmpt->tlx_ = tlx;
cmpt->tly_ = tly;
cmpt->hstep_ = hstep;
cmpt->vstep_ = vstep;
cmpt->width_ = width;
cmpt->height_ = height;
cmpt->prec_ = depth;
cmpt->sgnd_ = sgnd;
cmpt->stream_ = 0;
cmpt->cps_ = (depth + 7) / 8;
// Compute the number of samples in the image component, while protecting
// against overflow.
// size = cmpt->width_ * cmpt->height_ * cmpt->cps_;
if (!jas_safe_size_mul(cmpt->width_, cmpt->height_, &size) ||
!jas_safe_size_mul(size, cmpt->cps_, &size)) {
goto error;
}
cmpt->stream_ = (inmem) ? jas_stream_memopen2(0, size) :
jas_stream_tmpfile();
if (!cmpt->stream_) {
goto error;
}
/* Zero the component data. This isn't necessary, but it is
convenient for debugging purposes. */
/* Note: conversion of size - 1 to long can overflow */
if (size > 0) {
if (size - 1 > LONG_MAX) {
goto error;
}
if (jas_stream_seek(cmpt->stream_, size - 1, SEEK_SET) < 0 ||
jas_stream_putc(cmpt->stream_, 0) == EOF ||
jas_stream_seek(cmpt->stream_, 0, SEEK_SET) < 0) {
goto error;
}
}
return cmpt;
error:
if (cmpt) {
jas_image_cmpt_destroy(cmpt);
}
return 0;
} | Base | 1 |
void writeStats(Array& /*ret*/) override {
fprintf(stderr, "writeStats start\n");
// RetSame: the return value is the same instance every time
// HasThis: call has a this argument
// AllSame: all returns were the same data even though args are different
// MemberCount: number of different arg sets (including this)
fprintf(stderr, "Count Function MinSerLen MaxSerLen RetSame HasThis "
"AllSame MemberCount\n");
for (auto& me : m_memos) {
if (me.second.m_ignore) continue;
if (me.second.m_count == 1) continue;
int min_ser_len = 999999999;
int max_ser_len = 0;
int count = 0;
int member_count = 0;
bool all_same = true;
if (me.second.m_has_this) {
bool any_multiple = false;
auto& fr = me.second.m_member_memos.begin()->second.m_return_value;
member_count = me.second.m_member_memos.size();
for (auto& mme : me.second.m_member_memos) {
if (mme.second.m_return_value != fr) all_same = false;
count += mme.second.m_count;
auto ser_len = mme.second.m_return_value.length();
min_ser_len = std::min(min_ser_len, ser_len);
max_ser_len = std::max(max_ser_len, ser_len);
if (mme.second.m_count > 1) any_multiple = true;
}
if (!any_multiple && !all_same) continue;
} else {
min_ser_len = max_ser_len = me.second.m_return_value.length();
count = me.second.m_count;
all_same = me.second.m_ret_tv_same;
}
fprintf(stderr, "%d %s %d %d %s %s %s %d\n",
count, me.first.data(),
min_ser_len, max_ser_len,
me.second.m_ret_tv_same ? " true" : "false",
me.second.m_has_this ? " true" : "false",
all_same ? " true" : "false",
member_count
);
}
fprintf(stderr, "writeStats end\n");
} | Base | 1 |
TfLiteStatus GreaterEval(TfLiteContext* context, TfLiteNode* node) {
const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
bool requires_broadcast = !HaveSameShapes(input1, input2);
switch (input1->type) {
case kTfLiteFloat32:
Comparison<float, reference_ops::GreaterFn>(input1, input2, output,
requires_broadcast);
break;
case kTfLiteInt32:
Comparison<int32_t, reference_ops::GreaterFn>(input1, input2, output,
requires_broadcast);
break;
case kTfLiteInt64:
Comparison<int64_t, reference_ops::GreaterFn>(input1, input2, output,
requires_broadcast);
break;
case kTfLiteUInt8:
ComparisonQuantized<uint8_t, reference_ops::GreaterFn>(
input1, input2, output, requires_broadcast);
break;
case kTfLiteInt8:
ComparisonQuantized<int8_t, reference_ops::GreaterFn>(
input1, input2, output, requires_broadcast);
break;
default:
context->ReportError(context,
"Does not support type %d, requires float|int|uint8",
input1->type);
return kTfLiteError;
}
return kTfLiteOk;
} | Base | 1 |
mptctl_readtest (unsigned long arg)
{
struct mpt_ioctl_test __user *uarg = (void __user *) arg;
struct mpt_ioctl_test karg;
MPT_ADAPTER *ioc;
int iocnum;
if (copy_from_user(&karg, uarg, sizeof(struct mpt_ioctl_test))) {
printk(KERN_ERR MYNAM "%s@%d::mptctl_readtest - "
"Unable to read in mpt_ioctl_test struct @ %p\n",
__FILE__, __LINE__, uarg);
return -EFAULT;
}
if (((iocnum = mpt_verify_adapter(karg.hdr.iocnum, &ioc)) < 0) ||
(ioc == NULL)) {
printk(KERN_DEBUG MYNAM "%s::mptctl_readtest() @%d - ioc%d not found!\n",
__FILE__, __LINE__, iocnum);
return -ENODEV;
}
dctlprintk(ioc, printk(MYIOC_s_DEBUG_FMT "mptctl_readtest called.\n",
ioc->name));
/* Fill in the data and return the structure to the calling
* program
*/
#ifdef MFCNT
karg.chip_type = ioc->mfcnt;
#else
karg.chip_type = ioc->pcidev->device;
#endif
strncpy (karg.name, ioc->name, MPT_MAX_NAME);
karg.name[MPT_MAX_NAME-1]='\0';
strncpy (karg.product, ioc->prod_name, MPT_PRODUCT_LENGTH);
karg.product[MPT_PRODUCT_LENGTH-1]='\0';
/* Copy the data from kernel memory to user memory
*/
if (copy_to_user((char __user *)arg, &karg, sizeof(struct mpt_ioctl_test))) {
printk(MYIOC_s_ERR_FMT "%s@%d::mptctl_readtest - "
"Unable to write out mpt_ioctl_test struct @ %p\n",
ioc->name, __FILE__, __LINE__, uarg);
return -EFAULT;
}
return 0;
} | Class | 2 |
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
FillDiagHelper(input, output);
return kTfLiteOk;
} | Base | 1 |
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
const TfLiteTensor* cond_tensor =
GetInput(context, node, kInputConditionTensor);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
if (IsDynamicTensor(output)) {
TF_LITE_ENSURE_OK(context,
ResizeOutputTensor(context, cond_tensor, output));
}
TfLiteIntArray* dims = cond_tensor->dims;
if (dims->size == 0) {
// Scalar tensors are not supported.
TF_LITE_KERNEL_LOG(context, "Where op requires condition w/ rank > 0");
return kTfLiteError;
}
reference_ops::SelectTrueCoords(GetTensorShape(cond_tensor),
GetTensorData<bool>(cond_tensor),
GetTensorData<int64_t>(output));
return kTfLiteOk;
} | Base | 1 |
bool AdminRequestHandler::handleDumpStaticStringsRequest(
const std::string& /*cmd*/, const std::string& filename) {
auto const& list = lookupDefinedStaticStrings();
std::ofstream out(filename.c_str());
SCOPE_EXIT { out.close(); };
for (auto item : list) {
out << formatStaticString(item);
if (RuntimeOption::EvalPerfDataMap) {
auto const len = std::min<size_t>(item->size(), 255);
std::string str(item->data(), len);
// Only print the first line (up to 255 characters). Since we want '\0' in
// the list of characters to avoid, we need to use the version of
// `find_first_of()' with explicit length.
auto cutOffPos = str.find_first_of("\r\n", 0, 3);
if (cutOffPos != std::string::npos) str.erase(cutOffPos);
Debug::DebugInfo::recordDataMap(item->mutableData(),
item->mutableData() + item->size(),
"Str-" + str);
}
}
return true;
} | Base | 1 |
int GetU16BE (int nPos, bool *pbSuccess)
{
//*pbSuccess = true;
if ( nPos < 0 || nPos + 1 >= m_nLen)
{
*pbSuccess = false;
return 0;
}
int nRes = m_sFile[ nPos ];
nRes = (nRes << 8) + m_sFile[ nPos + 1 ];
return nRes;
} | Base | 1 |
TfLiteStatus GreaterEval(TfLiteContext* context, TfLiteNode* node) {
const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
bool requires_broadcast = !HaveSameShapes(input1, input2);
switch (input1->type) {
case kTfLiteFloat32:
Comparison<float, reference_ops::GreaterFn>(input1, input2, output,
requires_broadcast);
break;
case kTfLiteInt32:
Comparison<int32_t, reference_ops::GreaterFn>(input1, input2, output,
requires_broadcast);
break;
case kTfLiteInt64:
Comparison<int64_t, reference_ops::GreaterFn>(input1, input2, output,
requires_broadcast);
break;
case kTfLiteUInt8:
ComparisonQuantized<uint8_t, reference_ops::GreaterFn>(
input1, input2, output, requires_broadcast);
break;
case kTfLiteInt8:
ComparisonQuantized<int8_t, reference_ops::GreaterFn>(
input1, input2, output, requires_broadcast);
break;
default:
context->ReportError(context,
"Does not support type %d, requires float|int|uint8",
input1->type);
return kTfLiteError;
}
return kTfLiteOk;
} | Base | 1 |
static Variant HHVM_FUNCTION(simplexml_import_dom,
const Object& node,
const String& class_name /* = "SimpleXMLElement" */) {
auto domnode = Native::data<DOMNode>(node);
xmlNodePtr nodep = domnode->nodep();
if (nodep) {
if (nodep->doc == nullptr) {
raise_warning("Imported Node must have associated Document");
return init_null();
}
if (nodep->type == XML_DOCUMENT_NODE ||
nodep->type == XML_HTML_DOCUMENT_NODE) {
nodep = xmlDocGetRootElement((xmlDocPtr) nodep);
}
}
if (nodep && nodep->type == XML_ELEMENT_NODE) {
auto cls = class_from_name(class_name, "simplexml_import_dom");
if (!cls) {
return init_null();
}
Object obj = create_object(cls->nameStr(), Array(), false);
auto sxe = Native::data<SimpleXMLElement>(obj.get());
sxe->node = libxml_register_node(nodep);
return obj;
} else {
raise_warning("Invalid Nodetype to import");
return init_null();
}
return false;
} | Class | 2 |
RemoteDevicePropertiesWidget::RemoteDevicePropertiesWidget(QWidget *parent)
: QWidget(parent)
, modified(false)
, saveable(false)
{
setupUi(this);
if (qobject_cast<QTabWidget *>(parent)) {
verticalLayout->setMargin(4);
}
type->addItem(tr("Samba Share"), (int)Type_Samba);
type->addItem(tr("Samba Share (Auto-discover host and port)"), (int)Type_SambaAvahi);
type->addItem(tr("Secure Shell (sshfs)"), (int)Type_SshFs);
type->addItem(tr("Locally Mounted Folder"), (int)Type_File);
} | Class | 2 |
void Context::onDone() {
if (wasm_->onDone_) {
wasm_->onDone_(this, id_);
}
} | Base | 1 |
static NO_INLINE JsVar *jspGetNamedFieldInParents(JsVar *object, const char* name, bool returnName) {
// Now look in prototypes
JsVar * child = jspeiFindChildFromStringInParents(object, name);
/* Check for builtins via separate function
* This way we save on RAM for built-ins because everything comes out of program code */
if (!child) {
child = jswFindBuiltInFunction(object, name);
}
/* We didn't get here if we found a child in the object itself, so
* if we're here then we probably have the wrong name - so for example
* with `a.b = c;` could end up setting `a.prototype.b` (bug #360)
*
* Also we might have got a built-in, which wouldn't have a name on it
* anyway - so in both cases, strip the name if it is there, and create
* a new name that references the object we actually requested the
* member from..
*/
if (child && returnName) {
// Get rid of existing name
if (jsvIsName(child)) {
JsVar *t = jsvGetValueOfName(child);
jsvUnLock(child);
child = t;
}
// create a new name
JsVar *nameVar = jsvNewFromString(name);
JsVar *newChild = jsvCreateNewChild(object, nameVar, child);
jsvUnLock2(nameVar, child);
child = newChild;
}
// If not found and is the prototype, create it
if (!child) {
if (jsvIsFunction(object) && strcmp(name, JSPARSE_PROTOTYPE_VAR)==0) {
// prototype is supposed to be an object
JsVar *proto = jsvNewObject();
// make sure it has a 'constructor' variable that points to the object it was part of
jsvObjectSetChild(proto, JSPARSE_CONSTRUCTOR_VAR, object);
child = jsvAddNamedChild(object, proto, JSPARSE_PROTOTYPE_VAR);
jspEnsureIsPrototype(object, child);
jsvUnLock(proto);
} else if (strcmp(name, JSPARSE_INHERITS_VAR)==0) {
const char *objName = jswGetBasicObjectName(object);
if (objName) {
child = jspNewPrototype(objName);
}
}
}
return child;
} | Base | 1 |
inline TfLiteTensor* GetMutableInput(const TfLiteContext* context,
const TfLiteNode* node, int index) {
if (index >= 0 && index < node->inputs->size) {
const int tensor_index = node->inputs->data[index];
if (tensor_index != kTfLiteOptionalTensor) {
if (context->tensors != nullptr) {
return &context->tensors[tensor_index];
} else {
return context->GetTensor(context, tensor_index);
}
}
}
return nullptr;
} | Base | 1 |
SECURITY_STATUS SEC_ENTRY DeleteSecurityContext(PCtxtHandle phContext)
{
char* Name;
SECURITY_STATUS status;
SecurityFunctionTableA* table;
Name = (char*) sspi_SecureHandleGetUpperPointer(phContext);
if (!Name)
return SEC_E_SECPKG_NOT_FOUND;
table = sspi_GetSecurityFunctionTableAByNameA(Name);
if (!table)
return SEC_E_SECPKG_NOT_FOUND;
if (table->DeleteSecurityContext == NULL)
return SEC_E_UNSUPPORTED_FUNCTION;
status = table->DeleteSecurityContext(phContext);
return status;
} | Base | 1 |
inline typename V::MapType FBUnserializer<V>::unserializeMap() {
p_ += CODE_SIZE;
typename V::MapType ret = V::createMap();
size_t code = nextCode();
while (code != FB_SERIALIZE_STOP) {
switch (code) {
case FB_SERIALIZE_VARCHAR:
case FB_SERIALIZE_STRING:
{
auto key = unserializeString();
auto value = unserializeThing();
V::mapSet(ret, std::move(key), std::move(value));
}
break;
default:
{
auto key = unserializeInt64();
auto value = unserializeThing();
V::mapSet(ret, std::move(key), std::move(value));
}
}
code = nextCode();
}
p_ += CODE_SIZE;
return ret;
} | Class | 2 |
QString Helper::temporaryMountDevice(const QString &device, const QString &name, bool readonly)
{
QString mount_point = mountPoint(device);
if (!mount_point.isEmpty())
return mount_point;
mount_point = "%1/.%2/mount/%3";
const QStringList &tmp_paths = QStandardPaths::standardLocations(QStandardPaths::TempLocation);
mount_point = mount_point.arg(tmp_paths.isEmpty() ? "/tmp" : tmp_paths.first()).arg(qApp->applicationName()).arg(name);
if (!QDir::current().mkpath(mount_point)) {
dCError("mkpath \"%s\" failed", qPrintable(mount_point));
return QString();
}
if (!mountDevice(device, mount_point, readonly)) {
dCError("Mount the device \"%s\" to \"%s\" failed", qPrintable(device), qPrintable(mount_point));
return QString();
}
return mount_point;
} | Base | 1 |
static int64_t HHVM_FUNCTION(bccomp, const String& left, const String& right,
int64_t scale /* = -1 */) {
if (scale < 0) scale = BCG(bc_precision);
bc_num first, second;
bc_init_num(&first);
bc_init_num(&second);
bc_str2num(&first, (char*)left.data(), scale);
bc_str2num(&second, (char*)right.data(), scale);
int64_t ret = bc_compare(first, second);
bc_free_num(&first);
bc_free_num(&second);
return ret;
} | Base | 1 |
static const char *jsi_evalprint(Jsi_Value *v)
{
static char buf[100];
if (!v)
return "nil";
if (v->vt == JSI_VT_NUMBER) {
snprintf(buf, 100, "NUM:%" JSI_NUMGFMT " ", v->d.num);
} else if (v->vt == JSI_VT_BOOL) {
snprintf(buf, 100, "BOO:%d", v->d.val);
} else if (v->vt == JSI_VT_STRING) {
snprintf(buf, 100, "STR:'%s'", v->d.s.str);
} else if (v->vt == JSI_VT_VARIABLE) {
snprintf(buf, 100, "VAR:%p", v->d.lval);
} else if (v->vt == JSI_VT_NULL) {
snprintf(buf, 100, "NULL");
} else if (v->vt == JSI_VT_OBJECT) {
snprintf(buf, 100, "OBJ:%p", v->d.obj);
} else if (v->vt == JSI_VT_UNDEF) {
snprintf(buf, 100, "UNDEFINED");
}
return buf;
} | Base | 1 |
absl::Status IsSupported(const TfLiteContext* context,
const TfLiteNode* tflite_node,
const TfLiteRegistration* registration) final {
if (mirror_pad_) {
const TfLiteMirrorPaddingParams* tf_options;
RETURN_IF_ERROR(RetrieveBuiltinData(tflite_node, &tf_options));
if (tf_options->mode !=
TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingReflect) {
return absl::InvalidArgumentError(
"Only Reflective padding is supported for Mirror Pad operation.");
}
}
RETURN_IF_ERROR(CheckMaxSupportedOpVersion(registration, 2));
RETURN_IF_ERROR(CheckInputsOutputs(context, tflite_node,
/*runtime_inputs=*/1, /*outputs=*/1));
RETURN_IF_ERROR(CheckTensorIsAvailable(context, tflite_node, 1));
auto pad_tensor = tflite::GetInput(context, tflite_node, 1);
if (pad_tensor->dims->size != 2) {
return absl::InvalidArgumentError(absl::StrCat(
"Invalid paddings tensor dimension: expected 2 dim, got ",
pad_tensor->dims->size, " dim"));
}
bool supported =
pad_tensor->dims->data[0] == 3 || pad_tensor->dims->data[0] == 4;
if (!supported || pad_tensor->dims->data[1] != 2) {
return absl::InvalidArgumentError(absl::StrCat(
"Invalid paddings tensor shape: expected 4x2 or 3x2, got ",
pad_tensor->dims->data[0], "x", pad_tensor->dims->data[1]));
}
return absl::OkStatus();
} | Base | 1 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
const TfLiteTensor* cond_tensor =
GetInput(context, node, kInputConditionTensor);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
if (cond_tensor->type != kTfLiteBool) {
context->ReportError(context,
"Condition tensor must be of type bool, but saw '%s'.",
TfLiteTypeGetName(cond_tensor->type));
return kTfLiteError;
}
// As output will be a 2D tensor of indices, use int64 to be consistent with
// tensorflow.
output->type = kTfLiteInt64;
// Exit early if cond is a non-const tensor. Set output tensor to dynamic so
// output size can be determined in Eval.
if (!IsConstantTensor(cond_tensor)) {
SetTensorToDynamic(output);
return kTfLiteOk;
}
return ResizeOutputTensor(context, cond_tensor, output);
} | Base | 1 |
BinaryParameter::BinaryParameter(const char* name_, const char* desc_,
const void* v, int l, ConfigurationObject co)
: VoidParameter(name_, desc_, co), value(0), length(0), def_value((char*)v), def_length(l) {
if (l) {
value = new char[l];
length = l;
memcpy(value, v, l);
}
} | Base | 1 |
TfLiteStatus EvalHashtableSize(TfLiteContext* context, TfLiteNode* node) {
const TfLiteTensor* input_resource_id_tensor =
GetInput(context, node, kInputResourceIdTensor);
int resource_id = input_resource_id_tensor->data.i32[0];
TfLiteTensor* output_tensor = GetOutput(context, node, kOutputTensor);
auto* output_data = GetTensorData<std::int64_t>(output_tensor);
Subgraph* subgraph = reinterpret_cast<Subgraph*>(context->impl_);
auto& resources = subgraph->resources();
auto* lookup = resource::GetHashtableResource(&resources, resource_id);
TF_LITE_ENSURE(context, lookup != nullptr);
output_data[0] = lookup->Size();
return kTfLiteOk;
} | Base | 1 |
TfLiteStatus InitializeTemporaries(TfLiteContext* context, TfLiteNode* node,
OpContext* op_context) {
// Creates a temp index to iterate through input data.
OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
TfLiteIntArrayFree(node->temporaries);
node->temporaries = TfLiteIntArrayCreate(3);
node->temporaries->data[0] = op_data->scratch_tensor_index;
TfLiteTensor* scratch_tensor = GetTemporary(context, node, /*index=*/0);
scratch_tensor->type = kTfLiteInt32;
scratch_tensor->allocation_type = kTfLiteArenaRw;
TfLiteIntArray* index_size = TfLiteIntArrayCreate(1);
index_size->data[0] = NumDimensions(op_context->input);
TF_LITE_ENSURE_OK(context,
context->ResizeTensor(context, scratch_tensor, index_size));
// Creates a temp tensor to store resolved axis given input data.
node->temporaries->data[1] = op_data->scratch_tensor_index + 1;
TfLiteTensor* resolved_axis = GetTemporary(context, node, /*index=*/1);
resolved_axis->type = kTfLiteInt32;
// Creates a temp tensor to store temp sums when calculating mean.
node->temporaries->data[2] = op_data->scratch_tensor_index + 2;
TfLiteTensor* temp_sum = GetTemporary(context, node, /*index=*/2);
switch (op_context->input->type) {
case kTfLiteFloat32:
temp_sum->type = kTfLiteFloat32;
break;
case kTfLiteInt32:
temp_sum->type = kTfLiteInt64;
break;
case kTfLiteInt64:
temp_sum->type = kTfLiteInt64;
break;
case kTfLiteUInt8:
case kTfLiteInt8:
case kTfLiteInt16:
temp_sum->type = kTfLiteInt32;
break;
case kTfLiteBool:
temp_sum->type = kTfLiteBool;
break;
default:
return kTfLiteError;
}
return kTfLiteOk;
} | Base | 1 |
static int bson_append_string_base( bson *b, const char *name,
const char *value, int len, bson_type type ) {
int sl = len + 1;
if ( bson_check_string( b, ( const char * )value, sl - 1 ) == BSON_ERROR )
return BSON_ERROR;
if ( bson_append_estart( b, type, name, 4 + sl ) == BSON_ERROR ) {
return BSON_ERROR;
}
bson_append32( b , &sl );
bson_append( b , value , sl - 1 );
bson_append( b , "\0" , 1 );
return BSON_OK;
} | Base | 1 |
TfLiteTensor* GetOutput(TfLiteContext* context, const TfLiteNode* node,
int index) {
if (context->tensors != nullptr) {
return &context->tensors[node->outputs->data[index]];
} else {
return context->GetTensor(context, node->outputs->data[index]);
}
} | Base | 1 |
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
Subgraph* subgraph = reinterpret_cast<Subgraph*>(context->impl_);
const TfLiteTensor* input_resource_id_tensor =
GetInput(context, node, kInputVariableId);
const TfLiteTensor* input_value_tensor = GetInput(context, node, kInputValue);
int resource_id = input_resource_id_tensor->data.i32[0];
auto& resources = subgraph->resources();
resource::CreateResourceVariableIfNotAvailable(&resources, resource_id);
auto* variable = resource::GetResourceVariable(&resources, resource_id);
TF_LITE_ENSURE(context, variable != nullptr);
variable->AssignFrom(input_value_tensor);
return kTfLiteOk;
} | Base | 1 |
TfLiteRegistration OkOpRegistration() {
TfLiteRegistration reg = {nullptr, nullptr, nullptr, nullptr};
// Set output size to the input size in OkOp::Prepare(). Code exists to have
// a framework in Prepare. The input and output tensors are not used.
reg.prepare = [](TfLiteContext* context, TfLiteNode* node) {
const TfLiteTensor* in_tensor = GetInput(context, node, 0);
TfLiteTensor* out_tensor = GetOutput(context, node, 0);
TfLiteIntArray* new_size = TfLiteIntArrayCopy(in_tensor->dims);
return context->ResizeTensor(context, out_tensor, new_size);
};
reg.invoke = [](TfLiteContext* context, TfLiteNode* node) {
return kTfLiteOk;
};
return reg;
} | Base | 1 |
TfLiteStatus EvalImpl(TfLiteContext* context, TfLiteNode* node) {
auto* params =
reinterpret_cast<TfLiteDepthwiseConvParams*>(node->builtin_data);
OpData* data = reinterpret_cast<OpData*>(node->user_data);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
const TfLiteTensor* bias =
(NumInputs(node) == 3) ? GetInput(context, node, kBiasTensor) : nullptr;
TFLITE_DCHECK_EQ(input_type, input->type);
switch (input_type) { // Already know in/out types are same.
case kTfLiteFloat32:
if (filter->type == kTfLiteFloat32) {
return EvalFloat<kernel_type>(context, node, params, data, input,
filter, bias, output);
} else if (filter->type == kTfLiteInt8) {
return EvalHybridPerChannel<kernel_type>(context, node, params, data,
input, filter, bias, output);
} else {
TF_LITE_KERNEL_LOG(
context, "Type %s with filter type %s not currently supported.",
TfLiteTypeGetName(input->type), TfLiteTypeGetName(filter->type));
return kTfLiteError;
}
break;
case kTfLiteUInt8:
return EvalQuantized<kernel_type>(context, node, params, data, input,
filter, bias, output);
break;
case kTfLiteInt8:
return EvalQuantizedPerChannel<kernel_type>(context, node, params, data,
input, filter, bias, output);
break;
case kTfLiteInt16:
return EvalQuantizedPerChannel16x8(params, data, input, filter, bias,
output);
break;
default:
context->ReportError(context, "Type %d not currently supported.",
input->type);
return kTfLiteError;
}
} | Base | 1 |
set_ssl_ciphers(SCHANNEL_CRED *schannel_cred, char *ciphers,
int *algIds)
{
char *startCur = ciphers;
int algCount = 0;
while(startCur && (0 != *startCur) && (algCount < NUMOF_CIPHERS)) {
long alg = strtol(startCur, 0, 0);
if(!alg)
alg = get_alg_id_by_name(startCur);
if(alg)
algIds[algCount++] = alg;
else if(!strncmp(startCur, "USE_STRONG_CRYPTO",
sizeof("USE_STRONG_CRYPTO") - 1) ||
!strncmp(startCur, "SCH_USE_STRONG_CRYPTO",
sizeof("SCH_USE_STRONG_CRYPTO") - 1))
schannel_cred->dwFlags |= SCH_USE_STRONG_CRYPTO;
else
return CURLE_SSL_CIPHER;
startCur = strchr(startCur, ':');
if(startCur)
startCur++;
}
schannel_cred->palgSupportedAlgs = algIds;
schannel_cred->cSupportedAlgs = algCount;
return CURLE_OK;
} | Variant | 0 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
auto* params = reinterpret_cast<TfLiteMfccParams*>(node->user_data);
TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
const TfLiteTensor* input_wav = GetInput(context, node, kInputTensorWav);
const TfLiteTensor* input_rate = GetInput(context, node, kInputTensorRate);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
TF_LITE_ENSURE_EQ(context, NumDimensions(input_wav), 3);
TF_LITE_ENSURE_EQ(context, NumElements(input_rate), 1);
TF_LITE_ENSURE_TYPES_EQ(context, output->type, kTfLiteFloat32);
TF_LITE_ENSURE_TYPES_EQ(context, input_wav->type, output->type);
TF_LITE_ENSURE_TYPES_EQ(context, input_rate->type, kTfLiteInt32);
TfLiteIntArray* output_size = TfLiteIntArrayCreate(3);
output_size->data[0] = input_wav->dims->data[0];
output_size->data[1] = input_wav->dims->data[1];
output_size->data[2] = params->dct_coefficient_count;
return context->ResizeTensor(context, output, output_size);
} | Base | 1 |
bool CheckRegion(int nPos, int nSize)
{
return (nPos >= 0 && nPos + nSize >= nPos && nPos + nSize <= m_nLen);
} | Base | 1 |
TfLiteStatus InitializeTemporaries(TfLiteContext* context, TfLiteNode* node,
OpContext* op_context) {
// Creates a temp index to iterate through input data.
OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
TfLiteIntArrayFree(node->temporaries);
node->temporaries = TfLiteIntArrayCreate(3);
node->temporaries->data[0] = op_data->scratch_tensor_index;
TfLiteTensor* scratch_tensor = GetTemporary(context, node, /*index=*/0);
scratch_tensor->type = kTfLiteInt32;
scratch_tensor->allocation_type = kTfLiteArenaRw;
TfLiteIntArray* index_size = TfLiteIntArrayCreate(1);
index_size->data[0] = NumDimensions(op_context->input);
TF_LITE_ENSURE_OK(context,
context->ResizeTensor(context, scratch_tensor, index_size));
// Creates a temp tensor to store resolved axis given input data.
node->temporaries->data[1] = op_data->scratch_tensor_index + 1;
TfLiteTensor* resolved_axis = GetTemporary(context, node, /*index=*/1);
resolved_axis->type = kTfLiteInt32;
// Creates a temp tensor to store temp sums when calculating mean.
node->temporaries->data[2] = op_data->scratch_tensor_index + 2;
TfLiteTensor* temp_sum = GetTemporary(context, node, /*index=*/2);
switch (op_context->input->type) {
case kTfLiteFloat32:
temp_sum->type = kTfLiteFloat32;
break;
case kTfLiteInt32:
temp_sum->type = kTfLiteInt64;
break;
case kTfLiteInt64:
temp_sum->type = kTfLiteInt64;
break;
case kTfLiteUInt8:
case kTfLiteInt8:
case kTfLiteInt16:
temp_sum->type = kTfLiteInt32;
break;
case kTfLiteBool:
temp_sum->type = kTfLiteBool;
break;
default:
return kTfLiteError;
}
return kTfLiteOk;
} | Base | 1 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
auto* params = reinterpret_cast<TfLiteL2NormParams*>(node->builtin_data);
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
TF_LITE_ENSURE(context, NumDimensions(input) <= 4);
TF_LITE_ENSURE(context, output->type == kTfLiteFloat32 ||
output->type == kTfLiteUInt8 ||
output->type == kTfLiteInt8);
TF_LITE_ENSURE_TYPES_EQ(context, input->type, output->type);
if (output->type == kTfLiteUInt8 || output->type == kTfLiteInt8) {
TF_LITE_ENSURE_EQ(context, output->params.scale, (1. / 128.));
if (output->type == kTfLiteUInt8) {
TF_LITE_ENSURE_EQ(context, output->params.zero_point, 128);
}
if (output->type == kTfLiteInt8) {
TF_LITE_ENSURE_EQ(context, output->params.zero_point, 0);
}
}
// TODO(ahentz): For some reason our implementations don't support
// activations.
TF_LITE_ENSURE_EQ(context, params->activation, kTfLiteActNone);
TfLiteIntArray* output_size = TfLiteIntArrayCopy(input->dims);
return context->ResizeTensor(context, output, output_size);
} | Base | 1 |
Status OpLevelCostEstimator::PredictAvgPool(const OpContext& op_context,
NodeCosts* node_costs) const {
bool found_unknown_shapes = false;
const auto& op_info = op_context.op_info;
// x: op_info.inputs(0)
ConvolutionDimensions dims = OpDimensionsFromInputs(
op_info.inputs(0).shape(), op_info, &found_unknown_shapes);
// kx * ky - 1 additions and 1 multiplication per output.
int64_t ops = dims.batch * dims.ox * dims.oy * dims.oz * dims.kx * dims.ky;
node_costs->num_compute_ops = ops;
int64_t input_size;
if (dims.ky >= dims.sy) {
input_size = CalculateTensorSize(op_info.inputs(0), &found_unknown_shapes);
} else { // dims.ky < dims.sy
// vertical stride is larger than vertical kernel; assuming row-major
// format, skip unnecessary rows (or read every kx rows per sy rows, as the
// others are not used for output).
const auto data_size = DataTypeSize(BaseType(op_info.inputs(0).dtype()));
input_size = data_size * dims.batch * dims.ix * dims.ky * dims.oy * dims.iz;
}
node_costs->num_input_bytes_accessed = {input_size};
const int64_t output_size =
CalculateOutputSize(op_info, &found_unknown_shapes);
node_costs->num_output_bytes_accessed = {output_size};
node_costs->max_memory = output_size;
if (found_unknown_shapes) {
node_costs->inaccurate = true;
node_costs->num_nodes_with_unknown_shapes = 1;
}
return Status::OK();
} | Base | 1 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
const TfLiteTensor* input = GetInput(context, node, kInput);
const TfLiteTensor* axis = GetInput(context, node, kAxis);
TfLiteTensor* output = GetOutput(context, node, 0);
output->type = input->type;
if (IsConstantTensor(axis)) {
int axis_value;
TF_LITE_ENSURE_OK(context,
GetAxisValueFromTensor(context, *axis, &axis_value));
return ExpandTensorDim(context, *input, axis_value, output);
}
SetTensorToDynamic(output);
return kTfLiteOk;
} | Base | 1 |
inline bool loadModule(const char* filename, IR::Module& outModule)
{
// Read the specified file into an array.
std::vector<U8> fileBytes;
if(!loadFile(filename, fileBytes)) { return false; }
// If the file starts with the WASM binary magic number, load it as a binary irModule.
if(*(U32*)fileBytes.data() == 0x6d736100)
{ return loadBinaryModule(fileBytes.data(), fileBytes.size(), outModule); }
else
{
// Make sure the WAST file is null terminated.
fileBytes.push_back(0);
// Load it as a text irModule.
std::vector<WAST::Error> parseErrors;
if(!WAST::parseModule(
(const char*)fileBytes.data(), fileBytes.size(), outModule, parseErrors))
{
Log::printf(Log::error, "Error parsing WebAssembly text file:\n");
reportParseErrors(filename, parseErrors);
return false;
}
return true;
}
} | Base | 1 |
static int lookup1_values(int entries, int dim)
{
int r = (int) floor(exp((float) log((float) entries) / dim));
if ((int) floor(pow((float) r+1, dim)) <= entries) // (int) cast for MinGW warning;
++r; // floor() to avoid _ftol() when non-CRT
assert(pow((float) r+1, dim) > entries);
assert((int) floor(pow((float) r, dim)) <= entries); // (int),floor() as above
return r;
} | Base | 1 |
static float *get_window(vorb *f, int len)
{
len <<= 1;
if (len == f->blocksize_0) return f->window[0];
if (len == f->blocksize_1) return f->window[1];
assert(0);
return NULL;
} | Base | 1 |
static int decode_level3_header(LHAFileHeader **header, LHAInputStream *stream)
{
unsigned int header_len;
// The first field at the start of a level 3 header is supposed to
// indicate word size, with the idea being that the header format
// can be extended beyond 32-bit words in the future. In practise,
// nothing supports anything other than 32-bit (4 bytes), and neither
// do we.
if (lha_decode_uint16(&RAW_DATA(header, 0)) != 4) {
return 0;
}
// Read the full header.
if (!extend_raw_data(header, stream,
LEVEL_3_HEADER_LEN - RAW_DATA_LEN(header))) {
return 0;
}
// Read the header length field (including extended headers), and
// extend to this full length. Because this is a 32-bit value,
// we must place a sensible limit on the amount of data that will
// be read, to avoid possibly allocating gigabytes of memory.
header_len = lha_decode_uint32(&RAW_DATA(header, 24));
if (header_len > LEVEL_3_MAX_HEADER_LEN) {
return 0;
}
if (!extend_raw_data(header, stream,
header_len - RAW_DATA_LEN(header))) {
return 0;
}
// Compression method:
memcpy((*header)->compress_method, &RAW_DATA(header, 2), 5);
(*header)->compress_method[5] = '\0';
// File lengths:
(*header)->compressed_length = lha_decode_uint32(&RAW_DATA(header, 7));
(*header)->length = lha_decode_uint32(&RAW_DATA(header, 11));
// Unix-style timestamp.
(*header)->timestamp = lha_decode_uint32(&RAW_DATA(header, 15));
// CRC.
(*header)->crc = lha_decode_uint16(&RAW_DATA(header, 21));
// OS type:
(*header)->os_type = RAW_DATA(header, 23);
if (!decode_extended_headers(header, 28)) {
return 0;
}
return 1;
} | Base | 1 |
static String HHVM_FUNCTION(bcpow, const String& left, const String& right,
int64_t scale /* = -1 */) {
if (scale < 0) scale = BCG(bc_precision);
bc_num first, second, result;
bc_init_num(&first);
bc_init_num(&second);
bc_init_num(&result);
SCOPE_EXIT {
bc_free_num(&first);
bc_free_num(&second);
bc_free_num(&result);
};
php_str2num(&first, (char*)left.data());
php_str2num(&second, (char*)right.data());
bc_raise(first, second, &result, scale);
if (result->n_scale > scale) {
result->n_scale = scale;
}
String ret(bc_num2str(result), AttachString);
return ret;
} | Base | 1 |
StatusOr<FullTypeDef> SpecializeType(const AttrSlice& attrs,
const OpDef& op_def) {
FullTypeDef ft;
ft.set_type_id(TFT_PRODUCT);
for (int i = 0; i < op_def.output_arg_size(); i++) {
auto* t = ft.add_args();
*t = op_def.output_arg(i).experimental_full_type();
// Resolve dependent types. The convention for op registrations is to use
// attributes as type variables.
// See https://www.tensorflow.org/guide/create_op#type_polymorphism.
// Once the op signature can be defined entirely in FullType, this
// convention can be deprecated.
//
// Note: While this code performs some basic verifications, it generally
// assumes consistent op defs and attributes. If more complete
// verifications are needed, they should be done by separately, and in a
// way that can be reused for type inference.
for (int j = 0; j < t->args_size(); j++) {
auto* arg = t->mutable_args(i);
if (arg->type_id() == TFT_VAR) {
const auto* attr = attrs.Find(arg->s());
if (attr == nullptr) {
return Status(
error::INVALID_ARGUMENT,
absl::StrCat("Could not find an attribute for key ", arg->s()));
}
if (attr->value_case() == AttrValue::kList) {
const auto& attr_list = attr->list();
arg->set_type_id(TFT_PRODUCT);
for (int i = 0; i < attr_list.type_size(); i++) {
map_dtype_to_tensor(attr_list.type(i), arg->add_args());
}
} else if (attr->value_case() == AttrValue::kType) {
map_dtype_to_tensor(attr->type(), arg);
} else {
return Status(error::UNIMPLEMENTED,
absl::StrCat("unknown attribute type",
attrs.DebugString(), " key=", arg->s()));
}
arg->clear_s();
}
}
}
return ft;
} | Base | 1 |
const std::string& get_tenant() const {
ceph_assert(t != Wildcard);
return u.tenant;
} | Base | 1 |
static float *get_window(vorb *f, int len)
{
len <<= 1;
if (len == f->blocksize_0) return f->window[0];
if (len == f->blocksize_1) return f->window[1];
assert(0);
return NULL;
} | Base | 1 |
static int em_fxrstor(struct x86_emulate_ctxt *ctxt)
{
struct fxregs_state fx_state;
int rc;
rc = check_fxsr(ctxt);
if (rc != X86EMUL_CONTINUE)
return rc;
rc = segmented_read(ctxt, ctxt->memop.addr.mem, &fx_state, 512);
if (rc != X86EMUL_CONTINUE)
return rc;
if (fx_state.mxcsr >> 16)
return emulate_gp(ctxt, 0);
ctxt->ops->get_fpu(ctxt);
if (ctxt->mode < X86EMUL_MODE_PROT64)
rc = fxrstor_fixup(ctxt, &fx_state);
if (rc == X86EMUL_CONTINUE)
rc = asm_safe("fxrstor %[fx]", : [fx] "m"(fx_state));
ctxt->ops->put_fpu(ctxt);
return rc;
} | Class | 2 |
set<int> PipeSocketHandler::listen(const SocketEndpoint& endpoint) {
lock_guard<std::recursive_mutex> guard(globalMutex);
string pipePath = endpoint.name();
if (pipeServerSockets.find(pipePath) != pipeServerSockets.end()) {
throw runtime_error("Tried to listen twice on the same path");
}
sockaddr_un local;
int fd = socket(AF_UNIX, SOCK_STREAM, 0);
FATAL_FAIL(fd);
initServerSocket(fd);
local.sun_family = AF_UNIX; /* local is declared before socket() ^ */
strcpy(local.sun_path, pipePath.c_str());
unlink(local.sun_path);
FATAL_FAIL(::bind(fd, (struct sockaddr*)&local, sizeof(sockaddr_un)));
::listen(fd, 5);
#ifndef WIN32
FATAL_FAIL(::chmod(local.sun_path, S_IRUSR | S_IWUSR | S_IXUSR));
#endif
pipeServerSockets[pipePath] = set<int>({fd});
return pipeServerSockets[pipePath];
} | Base | 1 |
static int bson_append_estart( bson *b, int type, const char *name, const int dataSize ) {
const int len = strlen( name ) + 1;
if ( b->finished ) {
b->err |= BSON_ALREADY_FINISHED;
return BSON_ERROR;
}
if ( bson_ensure_space( b, 1 + len + dataSize ) == BSON_ERROR ) {
return BSON_ERROR;
}
if( bson_check_field_name( b, ( const char * )name, len - 1 ) == BSON_ERROR ) {
bson_builder_error( b );
return BSON_ERROR;
}
bson_append_byte( b, ( char )type );
bson_append( b, name, len );
return BSON_OK;
} | Base | 1 |
int64_t OpLevelCostEstimator::CalculateOutputSize(const OpInfo& op_info,
bool* found_unknown_shapes) {
int64_t total_output_size = 0;
// Use float as default for calculations.
for (const auto& output : op_info.outputs()) {
DataType dt = output.dtype();
const auto& original_output_shape = output.shape();
int64_t output_size = DataTypeSize(BaseType(dt));
int num_dims = std::max(1, original_output_shape.dim_size());
auto output_shape = MaybeGetMinimumShape(original_output_shape, num_dims,
found_unknown_shapes);
for (const auto& dim : output_shape.dim()) {
output_size *= dim.size();
}
total_output_size += output_size;
VLOG(1) << "Output Size: " << output_size
<< " Total Output Size:" << total_output_size;
}
return total_output_size;
} | Base | 1 |
std::string DecodeUnsafe(string_view encoded) {
std::string raw;
if (Decode(encoded, &raw)) {
return raw;
}
return ToString(encoded);
} | Base | 1 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
static const int kOutputUniqueTensor = 0;
static const int kOutputIndexTensor = 1;
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 2);
const TfLiteTensor* input = GetInput(context, node, 0);
TfLiteTensor* output_unique_tensor =
GetOutput(context, node, kOutputUniqueTensor);
TfLiteTensor* output_index_tensor =
GetOutput(context, node, kOutputIndexTensor);
// The op only supports 1D input.
TF_LITE_ENSURE_EQ(context, NumDimensions(input), 1);
TfLiteIntArray* output_index_shape = TfLiteIntArrayCopy(input->dims);
// The unique values are determined during evaluation, so we don't know yet
// the size of the output tensor.
SetTensorToDynamic(output_unique_tensor);
return context->ResizeTensor(context, output_index_tensor,
output_index_shape);
} | Base | 1 |
void RemoteDevicePropertiesWidget::checkSaveable()
{
RemoteFsDevice::Details det=details();
modified=det!=orig;
saveable=!det.isEmpty();
if (saveable && Type_SambaAvahi==type->itemData(type->currentIndex()).toInt()) {
saveable=!smbAvahiName->text().trimmed().isEmpty();
}
emit updated();
} | Base | 1 |
bool DNP3_Base::AddToBuffer(Endpoint* endp, int target_len, const u_char** data, int* len)
{
if ( ! target_len )
return true;
int to_copy = min(*len, target_len - endp->buffer_len);
memcpy(endp->buffer + endp->buffer_len, *data, to_copy);
*data += to_copy;
*len -= to_copy;
endp->buffer_len += to_copy;
return endp->buffer_len == target_len;
} | Class | 2 |
bool PackLinuxElf32::calls_crt1(Elf32_Rel const *rel, int sz)
{
if (!dynsym || !dynstr) {
return false;
}
for (unsigned relnum= 0; 0 < sz; (sz -= sizeof(Elf32_Rel)), ++rel, ++relnum) {
unsigned const symnum = get_te32(&rel->r_info) >> 8;
char const *const symnam = get_dynsym_name(symnum, relnum);
if (0==strcmp(symnam, "__libc_start_main") // glibc
|| 0==strcmp(symnam, "__libc_init") // Android
|| 0==strcmp(symnam, "__uClibc_main")
|| 0==strcmp(symnam, "__uClibc_start_main"))
return true;
}
return false;
} | Base | 1 |
void Logger::addMessage(const QString &message, const Log::MsgType &type)
{
QWriteLocker locker(&lock);
Log::Msg temp = { msgCounter++, QDateTime::currentMSecsSinceEpoch(), type, message };
m_messages.push_back(temp);
if (m_messages.size() >= MAX_LOG_MESSAGES)
m_messages.pop_front();
emit newLogMessage(temp);
} | Base | 1 |
R_API RBinJavaAttrInfo *r_bin_java_annotation_default_attr_new(RBinJavaObj *bin, ut8 *buffer, ut64 sz, ut64 buf_offset) {
ut64 offset = 0;
RBinJavaAttrInfo *attr = NULL;
attr = r_bin_java_default_attr_new (bin, buffer, sz, buf_offset);
offset += 6;
if (attr && sz >= offset) {
attr->type = R_BIN_JAVA_ATTR_TYPE_ANNOTATION_DEFAULT_ATTR;
attr->info.annotation_default_attr.default_value = r_bin_java_element_value_new (buffer + offset, sz - offset, buf_offset + offset);
if (attr->info.annotation_default_attr.default_value) {
offset += attr->info.annotation_default_attr.default_value->size;
}
}
r_bin_java_print_annotation_default_attr_summary (attr);
return attr;
} | Base | 1 |
Function *ESTreeIRGen::genGeneratorFunction(
Identifier originalName,
Variable *lazyClosureAlias,
ESTree::FunctionLikeNode *functionNode) {
assert(functionNode && "Function AST cannot be null");
// Build the outer function which creates the generator.
// Does not have an associated source range.
auto *outerFn = Builder.createGeneratorFunction(
originalName,
Function::DefinitionKind::ES5Function,
ESTree::isStrict(functionNode->strictness),
/* insertBefore */ nullptr);
auto *innerFn = genES5Function(
genAnonymousLabelName(originalName.isValid() ? originalName.str() : ""),
lazyClosureAlias,
functionNode,
true);
{
FunctionContext outerFnContext{this, outerFn, functionNode->getSemInfo()};
emitFunctionPrologue(
functionNode,
Builder.createBasicBlock(outerFn),
InitES5CaptureState::Yes,
DoEmitParameters::No);
// Create a generator function, which will store the arguments.
auto *gen = Builder.createCreateGeneratorInst(innerFn);
if (!hasSimpleParams(functionNode)) {
// If there are non-simple params, step the inner function once to
// initialize them.
Value *next = Builder.createLoadPropertyInst(gen, "next");
Builder.createCallInst(next, gen, {});
}
emitFunctionEpilogue(gen);
}
return outerFn;
} | Base | 1 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
auto* params =
reinterpret_cast<TfLiteDepthToSpaceParams*>(node->builtin_data);
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
TF_LITE_ENSURE_EQ(context, NumDimensions(input), 4);
auto data_type = output->type;
TF_LITE_ENSURE(context,
data_type == kTfLiteFloat32 || data_type == kTfLiteUInt8 ||
data_type == kTfLiteInt8 || data_type == kTfLiteInt32 ||
data_type == kTfLiteInt64);
TF_LITE_ENSURE_TYPES_EQ(context, input->type, output->type);
const int block_size = params->block_size;
const int input_height = input->dims->data[1];
const int input_width = input->dims->data[2];
const int input_channels = input->dims->data[3];
int output_height = input_height * block_size;
int output_width = input_width * block_size;
int output_channels = input_channels / block_size / block_size;
TF_LITE_ENSURE_EQ(context, input_height, output_height / block_size);
TF_LITE_ENSURE_EQ(context, input_width, output_width / block_size);
TF_LITE_ENSURE_EQ(context, input_channels,
output_channels * block_size * block_size);
TfLiteIntArray* output_size = TfLiteIntArrayCreate(4);
output_size->data[0] = input->dims->data[0];
output_size->data[1] = output_height;
output_size->data[2] = output_width;
output_size->data[3] = output_channels;
return context->ResizeTensor(context, output, output_size);
} | Base | 1 |
static int java_switch_op(RAnal *anal, RAnalOp *op, ut64 addr, const ut8 *data, int len) {
ut8 op_byte = data[0];
ut64 offset = addr - java_get_method_start ();
ut8 pos = (offset+1)%4 ? 1 + 4 - (offset+1)%4 : 1;
if (op_byte == 0xaa) {
// handle a table switch condition
if (pos + 8 > len) {
return op->size;
}
int min_val = (ut32)(UINT (data, pos + 4)),
max_val = (ut32)(UINT (data, pos + 8));
ut32 default_loc = (ut32) (UINT (data, pos)), cur_case = 0;
op->switch_op = r_anal_switch_op_new (addr, min_val, default_loc);
RAnalCaseOp *caseop = NULL;
pos += 12;
if (max_val > min_val && ((max_val - min_val)<(UT16_MAX/4))) {
//caseop = r_anal_switch_op_add_case(op->switch_op, addr+default_loc, -1, addr+offset);
for (cur_case = 0; cur_case <= max_val - min_val; pos += 4, cur_case++) {
//ut32 value = (ut32)(UINT (data, pos));
if (pos + 4 >= len) {
// switch is too big cant read further
break;
}
int offset = (int)(ut32)(R_BIN_JAVA_UINT (data, pos));
caseop = r_anal_switch_op_add_case (op->switch_op,
addr + pos, cur_case + min_val, addr + offset);
if (caseop) {
caseop->bb_ref_to = addr+offset;
caseop->bb_ref_from = addr; // TODO figure this one out
}
}
} else {
eprintf ("Invalid switch boundaries at 0x%"PFMT64x"\n", addr);
}
}
op->size = pos;
return op->size;
} | Base | 1 |
void HeaderTable::setCapacity(uint32_t capacity) {
auto oldCapacity = capacity_;
capacity_ = capacity;
if (capacity_ <= oldCapacity) {
evict(0);
} else {
auto oldTail = tail();
auto oldLength = table_.size();
uint32_t newLength = (capacity_ >> 5) + 1;
table_.resize(newLength);
if (size_ > 0 && oldTail > head_) {
// the list wrapped around, need to move oldTail..oldLength to the end of
// the now-larger table_
std::copy(table_.begin() + oldTail, table_.begin() + oldLength,
table_.begin() + newLength - (oldLength - oldTail));
// Update the names indecies that pointed to the old range
for (auto& names_it: names_) {
for (auto& idx: names_it.second) {
if (idx >= oldTail) {
DCHECK_LT(idx + (table_.size() - oldLength), table_.size());
idx += (table_.size() - oldLength);
} else {
// remaining indecies in the list were smaller than oldTail, so
// should be indexed from 0
break;
}
}
}
}
}
} | Variant | 0 |
int FdInStream::readWithTimeoutOrCallback(void* buf, int len, bool wait)
{
struct timeval before, after;
if (timing)
gettimeofday(&before, 0);
int n;
while (true) {
do {
fd_set fds;
struct timeval tv;
struct timeval* tvp = &tv;
if (!wait) {
tv.tv_sec = tv.tv_usec = 0;
} else if (timeoutms != -1) {
tv.tv_sec = timeoutms / 1000;
tv.tv_usec = (timeoutms % 1000) * 1000;
} else {
tvp = 0;
}
FD_ZERO(&fds);
FD_SET(fd, &fds);
n = select(fd+1, &fds, 0, 0, tvp);
} while (n < 0 && errno == EINTR);
if (n > 0) break;
if (n < 0) throw SystemException("select",errno);
if (!wait) return 0;
if (!blockCallback) throw TimedOut();
blockCallback->blockCallback();
}
do {
n = ::recv(fd, (char*)buf, len, 0);
} while (n < 0 && errno == EINTR);
if (n < 0) throw SystemException("read",errno);
if (n == 0) throw EndOfStream();
if (timing) {
gettimeofday(&after, 0);
int newTimeWaited = ((after.tv_sec - before.tv_sec) * 10000 +
(after.tv_usec - before.tv_usec) / 100);
int newKbits = n * 8 / 1000;
// limit rate to between 10kbit/s and 40Mbit/s
if (newTimeWaited > newKbits*1000) newTimeWaited = newKbits*1000;
if (newTimeWaited < newKbits/4) newTimeWaited = newKbits/4;
timeWaitedIn100us += newTimeWaited;
timedKbits += newKbits;
}
return n;
} | Base | 1 |
TEST_F(ListenerManagerImplQuicOnlyTest, QuicListenerFactoryWithWrongTransportSocket) {
const std::string yaml = TestEnvironment::substitute(R"EOF(
address:
socket_address:
address: 127.0.0.1
protocol: UDP
port_value: 1234
filter_chains:
- filter_chain_match:
transport_protocol: "quic"
filters: []
transport_socket:
name: envoy.transport_sockets.quic
typed_config:
"@type": type.googleapis.com/envoy.extensions.transport_sockets.tls.v3.DownstreamTlsContext
common_tls_context:
tls_certificates:
- certificate_chain:
filename: "{{ test_rundir }}/test/extensions/transport_sockets/tls/test_data/san_uri_cert.pem"
private_key:
filename: "{{ test_rundir }}/test/extensions/transport_sockets/tls/test_data/san_uri_key.pem"
validation_context:
trusted_ca:
filename: "{{ test_rundir }}/test/extensions/transport_sockets/tls/test_data/ca_cert.pem"
match_subject_alt_names:
- exact: localhost
- exact: 127.0.0.1
udp_listener_config:
quic_options: {}
)EOF",
Network::Address::IpVersion::v4);
envoy::config::listener::v3::Listener listener_proto = parseListenerFromV3Yaml(yaml);
#if defined(ENVOY_ENABLE_QUIC)
EXPECT_THROW_WITH_REGEX(manager_->addOrUpdateListener(listener_proto, "", true), EnvoyException,
"wrong transport socket config specified for quic transport socket");
#else
EXPECT_THROW_WITH_REGEX(manager_->addOrUpdateListener(listener_proto, "", true), EnvoyException,
"QUIC is configured but not enabled in the build.");
#endif
} | Base | 1 |
R_API RBinJavaAttrInfo *r_bin_java_read_next_attr_from_buffer(ut8 *buffer, st64 sz, st64 buf_offset) {
RBinJavaAttrInfo *attr = NULL;
char *name = NULL;
ut64 offset = 0;
ut16 name_idx;
st64 nsz;
RBinJavaAttrMetas *type_info = NULL;
if (!buffer || ((int) sz) < 4 || buf_offset < 0) {
eprintf ("r_bin_Java_read_next_attr_from_buffer: invalid buffer size %d\n", (int) sz);
return NULL;
}
name_idx = R_BIN_JAVA_USHORT (buffer, offset);
offset += 2;
nsz = R_BIN_JAVA_UINT (buffer, offset);
offset += 4;
name = r_bin_java_get_utf8_from_bin_cp_list (R_BIN_JAVA_GLOBAL_BIN, name_idx);
if (!name) {
name = strdup ("unknown");
}
IFDBG eprintf("r_bin_java_read_next_attr: name_idx = %d is %s\n", name_idx, name);
type_info = r_bin_java_get_attr_type_by_name (name);
if (type_info) {
IFDBG eprintf("Typeinfo: %s, was %s\n", type_info->name, name);
// printf ("SZ %d %d %d\n", nsz, sz, buf_offset);
if (nsz > sz) {
free (name);
return NULL;
}
if ((attr = type_info->allocs->new_obj (buffer, nsz, buf_offset))) {
attr->metas->ord = (R_BIN_JAVA_GLOBAL_BIN->attr_idx++);
}
} else {
eprintf ("r_bin_java_read_next_attr_from_buffer: Cannot find type_info for %s\n", name);
}
free (name);
return attr;
} | Base | 1 |
int FileInStream::overrun(int itemSize, int nItems, bool wait)
{
if (itemSize > (int)sizeof(b))
throw Exception("FileInStream overrun: max itemSize exceeded");
if (end - ptr != 0)
memmove(b, ptr, end - ptr);
end -= ptr - b;
ptr = b;
while (end < b + itemSize) {
size_t n = fread((U8 *)end, b + sizeof(b) - end, 1, file);
if (n == 0) {
if (ferror(file))
throw SystemException("fread", errno);
if (feof(file))
throw EndOfStream();
return 0;
}
end += b + sizeof(b) - end;
}
if (itemSize * nItems > end - ptr)
nItems = (end - ptr) / itemSize;
return nItems;
} | Base | 1 |
static int lookup1_values(int entries, int dim)
{
int r = (int) floor(exp((float) log((float) entries) / dim));
if ((int) floor(pow((float) r+1, dim)) <= entries) // (int) cast for MinGW warning;
++r; // floor() to avoid _ftol() when non-CRT
assert(pow((float) r+1, dim) > entries);
assert((int) floor(pow((float) r, dim)) <= entries); // (int),floor() as above
return r;
} | Base | 1 |
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
// Reinterprete the opaque data provided by user.
OpData* data = reinterpret_cast<OpData*>(node->user_data);
const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
TF_LITE_ENSURE_TYPES_EQ(context, input1->type, input2->type);
const TfLiteType type = input1->type;
switch (type) {
case kTfLiteFloat32:
case kTfLiteInt32:
break;
default:
context->ReportError(context, "Type '%s' is not supported by floor_div.",
TfLiteTypeGetName(type));
return kTfLiteError;
}
output->type = type;
data->requires_broadcast = !HaveSameShapes(input1, input2);
TfLiteIntArray* output_size = nullptr;
if (data->requires_broadcast) {
TF_LITE_ENSURE_OK(context, CalculateShapeForBroadcast(
context, input1, input2, &output_size));
} else {
output_size = TfLiteIntArrayCopy(input1->dims);
}
return context->ResizeTensor(context, output, output_size);
} | Base | 1 |
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
const TfLiteTensor* input = GetInput(context, node, kInputTensor);
const TfLiteTensor* diag = GetInput(context, node, kDiagonalTensor);
FillDiagHelper(input, diag, output);
return kTfLiteOk;
} | Base | 1 |
void CalculateOutputIndexRowSplit(
const RowPartitionTensor& row_split,
const vector<INDEX_TYPE>& parent_output_index,
INDEX_TYPE output_index_multiplier, INDEX_TYPE output_size,
vector<INDEX_TYPE>* result) {
INDEX_TYPE row_split_size = row_split.size();
if (row_split_size > 0) {
result->reserve(row_split(row_split_size - 1));
}
for (INDEX_TYPE i = 0; i < row_split_size - 1; ++i) {
INDEX_TYPE row_length = row_split(i + 1) - row_split(i);
INDEX_TYPE real_length = std::min(output_size, row_length);
INDEX_TYPE parent_output_index_current = parent_output_index[i];
if (parent_output_index_current == -1) {
real_length = 0;
}
for (INDEX_TYPE j = 0; j < real_length; ++j) {
result->push_back(parent_output_index_current);
parent_output_index_current += output_index_multiplier;
}
for (INDEX_TYPE j = 0; j < row_length - real_length; ++j) {
result->push_back(-1);
}
}
if (row_split_size > 0) {
DCHECK_EQ(result->size(), row_split(row_split_size - 1));
}
} | Base | 1 |
jas_matrix_t *jas_matrix_create(int numrows, int numcols)
{
jas_matrix_t *matrix;
int i;
size_t size;
matrix = 0;
if (numrows < 0 || numcols < 0) {
goto error;
}
if (!(matrix = jas_malloc(sizeof(jas_matrix_t)))) {
goto error;
}
matrix->flags_ = 0;
matrix->numrows_ = numrows;
matrix->numcols_ = numcols;
matrix->rows_ = 0;
matrix->maxrows_ = numrows;
matrix->data_ = 0;
matrix->datasize_ = 0;
// matrix->datasize_ = numrows * numcols;
if (!jas_safe_size_mul(numrows, numcols, &size)) {
goto error;
}
matrix->datasize_ = size;
if (matrix->maxrows_ > 0) {
if (!(matrix->rows_ = jas_alloc2(matrix->maxrows_,
sizeof(jas_seqent_t *)))) {
goto error;
}
}
if (matrix->datasize_ > 0) {
if (!(matrix->data_ = jas_alloc2(matrix->datasize_,
sizeof(jas_seqent_t)))) {
goto error;
}
}
for (i = 0; i < numrows; ++i) {
matrix->rows_[i] = &matrix->data_[i * matrix->numcols_];
}
for (i = 0; i < matrix->datasize_; ++i) {
matrix->data_[i] = 0;
}
matrix->xstart_ = 0;
matrix->ystart_ = 0;
matrix->xend_ = matrix->numcols_;
matrix->yend_ = matrix->numrows_;
return matrix;
error:
if (matrix) {
jas_matrix_destroy(matrix);
}
return 0;
} | Base | 1 |
Status CreateTempFile(Env* env, float value, uint64 size, string* filename) {
const string dir = testing::TmpDir();
*filename = io::JoinPath(dir, strings::StrCat("file_", value));
std::unique_ptr<WritableFile> file;
TF_RETURN_IF_ERROR(env->NewWritableFile(*filename, &file));
for (uint64 i = 0; i < size; ++i) {
StringPiece sp(static_cast<char*>(static_cast<void*>(&value)),
sizeof(value));
TF_RETURN_IF_ERROR(file->Append(sp));
}
TF_RETURN_IF_ERROR(file->Close());
return Status::OK();
} | Base | 1 |
Status OpLevelCostEstimator::PredictFusedBatchNormGrad(
const OpContext& op_context, NodeCosts* node_costs) const {
bool found_unknown_shapes = false;
const auto& op_info = op_context.op_info;
// y_backprop: op_info.inputs(0)
// x: op_info.inputs(1)
// scale: op_info.inputs(2)
// mean: op_info.inputs(3)
// variance or inverse of variance: op_info.inputs(4)
ConvolutionDimensions dims = OpDimensionsFromInputs(
op_info.inputs(1).shape(), op_info, &found_unknown_shapes);
int64_t ops = 0;
const auto rsqrt_cost = Eigen::internal::functor_traits<
Eigen::internal::scalar_rsqrt_op<float>>::Cost;
ops = dims.iz * (dims.batch * dims.ix * dims.iy * 11 + 5 + rsqrt_cost);
node_costs->num_compute_ops = ops;
const int64_t size_nhwc =
CalculateTensorSize(op_info.inputs(1), &found_unknown_shapes);
const int64_t size_c =
CalculateTensorSize(op_info.inputs(2), &found_unknown_shapes);
// TODO(dyoon): fix missing memory cost for variance input (size_c) and
// yet another read of y_backprop (size_nhwc) internally.
node_costs->num_input_bytes_accessed = {size_nhwc, size_nhwc, size_c, size_c};
node_costs->num_output_bytes_accessed = {size_nhwc, size_c, size_c};
// FusedBatchNormGrad has to read y_backprop internally.
node_costs->internal_read_bytes = size_nhwc;
node_costs->max_memory = node_costs->num_total_output_bytes();
if (found_unknown_shapes) {
node_costs->inaccurate = true;
node_costs->num_nodes_with_unknown_shapes = 1;
}
return Status::OK();
} | Base | 1 |
QString Helper::temporaryMountDevice(const QString &device, const QString &name, bool readonly)
{
QString mount_point = mountPoint(device);
if (!mount_point.isEmpty())
return mount_point;
mount_point = "%1/.%2/mount/%3";
const QStringList &tmp_paths = QStandardPaths::standardLocations(QStandardPaths::TempLocation);
mount_point = mount_point.arg(tmp_paths.isEmpty() ? "/tmp" : tmp_paths.first()).arg(qApp->applicationName()).arg(name);
if (!QDir::current().mkpath(mount_point)) {
dCError("mkpath \"%s\" failed", qPrintable(mount_point));
return QString();
}
if (!mountDevice(device, mount_point, readonly)) {
dCError("Mount the device \"%s\" to \"%s\" failed", qPrintable(device), qPrintable(mount_point));
return QString();
}
return mount_point;
} | Base | 1 |
Json::Value SGXWalletServer::calculateAllBLSPublicKeysImpl(const Json::Value& publicShares, int t, int n) {
spdlog::info("Entering {}", __FUNCTION__);
INIT_RESULT(result)
try {
if (!check_n_t(t, n)) {
throw SGXException(INVALID_DKG_PARAMS, "Invalid DKG parameters: n or t ");
}
if (!publicShares.isArray()) {
throw SGXException(INVALID_DKG_PARAMS, "Invalid public shares format");
}
if (publicShares.size() != (uint64_t) n) {
throw SGXException(INVALID_DKG_PARAMS, "Invalid length of public shares");
}
for (int i = 0; i < n; ++i) {
if (!publicShares[i].isString()) {
throw SGXException(INVALID_DKG_PARAMS, "Invalid public shares parts format");
}
if (publicShares[i].asString().length() != (uint64_t) 256 * t) {
throw SGXException(INVALID_DKG_PARAMS, "Invalid length of public shares parts");
}
}
vector<string> public_shares(n);
for (int i = 0; i < n; ++i) {
public_shares[i] = publicShares[i].asString();
}
vector<string> public_keys = calculateAllBlsPublicKeys(public_shares);
if (public_keys.size() != n) {
throw SGXException(UNKNOWN_ERROR, "");
}
for (int i = 0; i < n; ++i) {
result["publicKeys"][i] = public_keys[i];
}
} HANDLE_SGX_EXCEPTION(result)
RETURN_SUCCESS(result);
} | Base | 1 |
uint64_t HeaderMapImpl::byteSize() const {
uint64_t byte_size = 0;
for (const HeaderEntryImpl& header : headers_) {
byte_size += header.key().size();
byte_size += header.value().size();
}
return byte_size;
} | Class | 2 |
void CalculateOutputIndexValueRowID(
const RowPartitionTensor& value_rowids,
const vector<INDEX_TYPE>& parent_output_index,
INDEX_TYPE output_index_multiplier, INDEX_TYPE output_size,
vector<INDEX_TYPE>* result) {
const INDEX_TYPE index_size = value_rowids.size();
result->reserve(index_size);
if (index_size == 0) {
return;
}
INDEX_TYPE current_output_column = 0;
INDEX_TYPE current_value_rowid = value_rowids(0);
DCHECK_LT(current_value_rowid, parent_output_index.size());
INDEX_TYPE current_output_index = parent_output_index[current_value_rowid];
result->push_back(current_output_index);
for (INDEX_TYPE i = 1; i < index_size; ++i) {
INDEX_TYPE next_value_rowid = value_rowids(i);
if (next_value_rowid == current_value_rowid) {
if (current_output_index >= 0) {
++current_output_column;
if (current_output_column < output_size) {
current_output_index += output_index_multiplier;
} else {
current_output_index = -1;
}
}
} else {
current_output_column = 0;
current_value_rowid = next_value_rowid;
DCHECK_LT(next_value_rowid, parent_output_index.size());
current_output_index = parent_output_index[next_value_rowid];
}
result->push_back(current_output_index);
}
DCHECK_EQ(result->size(), value_rowids.size());
} | Base | 1 |
int length() const {
return m_str ? m_str->size() : 0;
} | Base | 1 |
TEST_F(RouterTest, MissingRequiredHeaders) {
NiceMock<Http::MockRequestEncoder> encoder;
Http::ResponseDecoder* response_decoder = nullptr;
expectNewStreamWithImmediateEncoder(encoder, &response_decoder, Http::Protocol::Http10);
expectResponseTimerCreate();
Http::TestRequestHeaderMapImpl headers;
HttpTestUtility::addDefaultHeaders(headers);
headers.removeMethod();
EXPECT_CALL(encoder, encodeHeaders(_, _))
.WillOnce(Invoke([](const Http::RequestHeaderMap& headers, bool) -> Http::Status {
return Http::HeaderUtility::checkRequiredRequestHeaders(headers);
}));
EXPECT_CALL(
callbacks_,
sendLocalReply(Http::Code::ServiceUnavailable,
testing::Eq("missing required header: :method"), _, _,
"filter_removed_required_request_headers{missing_required_header:_:method}"))
.WillOnce(testing::InvokeWithoutArgs([] {}));
router_.decodeHeaders(headers, true);
router_.onDestroy();
} | Class | 2 |
static __forceinline void draw_line(float *output, int x0, int y0, int x1, int y1, int n)
{
int dy = y1 - y0;
int adx = x1 - x0;
int ady = abs(dy);
int base;
int x=x0,y=y0;
int err = 0;
int sy;
#ifdef STB_VORBIS_DIVIDE_TABLE
if (adx < DIVTAB_DENOM && ady < DIVTAB_NUMER) {
if (dy < 0) {
base = -integer_divide_table[ady][adx];
sy = base-1;
} else {
base = integer_divide_table[ady][adx];
sy = base+1;
}
} else {
base = dy / adx;
if (dy < 0)
sy = base - 1;
else
sy = base+1;
}
#else
base = dy / adx;
if (dy < 0)
sy = base - 1;
else
sy = base+1;
#endif
ady -= abs(base) * adx;
if (x1 > n) x1 = n;
if (x < x1) {
LINE_OP(output[x], inverse_db_table[y]);
for (++x; x < x1; ++x) {
err += ady;
if (err >= adx) {
err -= adx;
y += sy;
} else
y += base;
LINE_OP(output[x], inverse_db_table[y]);
}
}
} | Base | 1 |
void CLASS panasonic_load_raw()
{
int row, col, i, j, sh = 0, pred[2], nonz[2];
pana_bits(0);
for (row = 0; row < height; row++)
{
#ifdef LIBRAW_LIBRARY_BUILD
checkCancel();
#endif
for (col = 0; col < raw_width; col++)
{
if ((i = col % 14) == 0)
pred[0] = pred[1] = nonz[0] = nonz[1] = 0;
if (i % 3 == 2)
sh = 4 >> (3 - pana_bits(2));
if (nonz[i & 1])
{
if ((j = pana_bits(8)))
{
if ((pred[i & 1] -= 0x80 << sh) < 0 || sh == 4)
pred[i & 1] &= ~((~0u) << sh);
pred[i & 1] += j << sh;
}
}
else if ((nonz[i & 1] = pana_bits(8)) || i > 11)
pred[i & 1] = nonz[i & 1] << 4 | pana_bits(4);
if ((RAW(row, col) = pred[col & 1]) > 4098 && col < width)
derror();
}
}
} | Class | 2 |
inline bool ShapeIsVector(TfLiteContext* context, TfLiteNode* node) {
const TfLiteTensor* shape = GetInput(context, node, kShapeTensor);
return (shape->dims->size == 1 && shape->type == kTfLiteInt32);
} | Base | 1 |
static String HHVM_FUNCTION(bcadd, const String& left, const String& right,
int64_t scale /* = -1 */) {
if (scale < 0) scale = BCG(bc_precision);
bc_num first, second, result;
bc_init_num(&first);
bc_init_num(&second);
bc_init_num(&result);
php_str2num(&first, (char*)left.data());
php_str2num(&second, (char*)right.data());
bc_add(first, second, &result, scale);
if (result->n_scale > scale) {
result->n_scale = scale;
}
String ret(bc_num2str(result), AttachString);
bc_free_num(&first);
bc_free_num(&second);
bc_free_num(&result);
return ret;
} | Base | 1 |
unsigned int GetU32BE (int nPos, bool *pbSuccess)
{
//*pbSuccess = true;
if ( nPos < 0 || nPos + 3 >= m_nLen )
{
*pbSuccess = false;
return 0;
}
unsigned int nRes = m_sFile[nPos];
nRes = (nRes << 8) + m_sFile[nPos + 1];
nRes = (nRes << 8) + m_sFile[nPos + 2];
nRes = (nRes << 8) + m_sFile[nPos + 3];
return nRes;
} | Base | 1 |
static int intel_pmu_handle_irq(struct pt_regs *regs)
{
struct perf_sample_data data;
struct cpu_hw_events *cpuc;
int bit, loops;
u64 status;
int handled;
perf_sample_data_init(&data, 0);
cpuc = &__get_cpu_var(cpu_hw_events);
/*
* Some chipsets need to unmask the LVTPC in a particular spot
* inside the nmi handler. As a result, the unmasking was pushed
* into all the nmi handlers.
*
* This handler doesn't seem to have any issues with the unmasking
* so it was left at the top.
*/
apic_write(APIC_LVTPC, APIC_DM_NMI);
intel_pmu_disable_all();
handled = intel_pmu_drain_bts_buffer();
status = intel_pmu_get_status();
if (!status) {
intel_pmu_enable_all(0);
return handled;
}
loops = 0;
again:
intel_pmu_ack_status(status);
if (++loops > 100) {
WARN_ONCE(1, "perfevents: irq loop stuck!\n");
perf_event_print_debug();
intel_pmu_reset();
goto done;
}
inc_irq_stat(apic_perf_irqs);
intel_pmu_lbr_read();
/*
* PEBS overflow sets bit 62 in the global status register
*/
if (__test_and_clear_bit(62, (unsigned long *)&status)) {
handled++;
x86_pmu.drain_pebs(regs);
}
for_each_set_bit(bit, (unsigned long *)&status, X86_PMC_IDX_MAX) {
struct perf_event *event = cpuc->events[bit];
handled++;
if (!test_bit(bit, cpuc->active_mask))
continue;
if (!intel_pmu_save_and_restart(event))
continue;
data.period = event->hw.last_period;
if (perf_event_overflow(event, 1, &data, regs))
x86_pmu_stop(event, 0);
}
/*
* Repeat if there is more work to be done:
*/
status = intel_pmu_get_status();
if (status)
goto again;
done:
intel_pmu_enable_all(0);
return handled;
} | Class | 2 |
it "stores the list of seeds" do
cluster.seeds.should eq ["127.0.0.1:27017", "127.0.0.1:27018"]
end | Class | 2 |
it "changes the $orderby" do
query.sort(a: 1)
query.sort(a: 2)
query.operation.selector.should eq(
"$query" => selector,
"$orderby" => { a: 2 }
)
end | Class | 2 |
def html_escape(s)
s = s.to_s
if s.html_safe?
s
else
s.gsub(/[&"><]/) { |special| HTML_ESCAPE[special] }.html_safe
end
end | Base | 1 |
def config_backup(params, request, session)
if params[:name]
code, response = send_request_with_token(
session, params[:name], 'config_backup', true
)
else
if not allowed_for_local_cluster(session, Permissions::FULL)
return 403, 'Permission denied'
end
$logger.info "Backup node configuration"
stdout, stderr, retval = run_cmd(session, PCS, "config", "backup")
if retval == 0
$logger.info "Backup successful"
return [200, stdout]
end
$logger.info "Error during backup: #{stderr.join(' ').strip()}"
return [400, "Unable to backup node: #{stderr.join(' ')}"]
end
end | Compound | 4 |
def self.execute_action_move(mail_filter, email, val)
mail_folder_id = val
mail_folder = MailFolder.find_by_id(mail_folder_id)
if !mail_folder.nil? and (mail_folder.user_id == email.user_id)
email.update_attribute(:mail_folder_id, mail_folder_id)
end
return true
end | Base | 1 |
it 'is possible to specify a custom formatter' do
get '/'
expect(last_response.body).to eq('{:custom_formatter=>"rain!"}')
end | Base | 1 |
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