static void tensorEye(rpc::RPCMessage& raw_message) {
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
long n = unpackInteger(raw_message);
long m = unpackInteger(raw_message);
finalize(raw_message);
tensor->eye(n, m);
}
static void tensorMean(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
int dimension = unpackInteger(raw_message);
int keepdim = unpackInteger(raw_message);
finalize(raw_message);
r->mean(*t, dimension, keepdim);
}
static void tensorSort(rpc::RPCMessage& raw_message) {
thpp::Tensor *rt = unpackRetrieveTensor(raw_message);
thpp::Tensor *ri = unpackRetrieveTensor(raw_message);
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
int dimension = unpackInteger(raw_message);
int desc = unpackInteger(raw_message);
finalize(raw_message);
rt->sort(*ri, *tensor, dimension, desc);
}
static void tensorStd(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
int dimension = unpackInteger(raw_message);
int biased = unpackInteger(raw_message);
int keepdim = unpackInteger(raw_message);
finalize(raw_message);
r->std(*t, dimension, biased, keepdim);
}
static void tensorCatArray(rpc::RPCMessage& raw_message) {
thpp::Tensor *result = unpackRetrieveTensor(raw_message);
int numInputs = unpackInteger(raw_message);
std::vector<thpp::Tensor*> inputs(numInputs);
for (std::size_t i = 0; i < numInputs; i++)
inputs[i] = unpackRetrieveTensor(raw_message);
int dimension = unpackInteger(raw_message);
finalize(raw_message);
result->catArray(inputs, dimension);
}
static void tensorTopk(rpc::RPCMessage& raw_message) {
thpp::Tensor *rt = unpackRetrieveTensor(raw_message);
thpp::Tensor *ri = unpackRetrieveTensor(raw_message);
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
long k = unpackInteger(raw_message);
int dimension = unpackInteger(raw_message);
int dir = unpackInteger(raw_message);
int sorted = unpackInteger(raw_message);
finalize(raw_message);
rt->topk(*ri, *tensor, k, dimension, dir, sorted);
}
static void tensorTriu(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
long k = unpackInteger(raw_message);
finalize(raw_message);
r->triu(*t, k);
}
static void tensorRandperm(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Generator *_generator = unpackRetrieveGenerator(raw_message);
long n = unpackInteger(raw_message);
finalize(raw_message);
r->randperm(*_generator, n);
}
/** Unpack an entire setting description from the buffer
*
* @param pBuffer the buffer to unpack from
* @param index the index in the buffer to start at
* @param size the size of the buffer in bytes
* @param setting the structure to hold the setting value
*
* @return the new index for the next piece of data or 0 if an error occurs.
*/
static int unpackSetting(unsigned char *pBuffer, int index, int size, SettingDescription &setting) {
if ((index + 1)>=size) // Make sure we have the type modifier at least
return 0;
// 1 byte for type
setting.typeAndModifier = pBuffer[index++];
// The name
if ((index=unpackString(pBuffer, index, size, &setting.name))<=0)
return index;
// And the value itself
switch(setting.typeAndModifier & SETTING_TYPE_MASK) {
case StringSetting:
index = unpackString(pBuffer, index, size, &setting.value.string);
break;
case IntegerSetting:
index = unpackInteger(pBuffer, index, size, setting.value.integer);
break;
case BooleanSetting:
index = unpackBoolean(pBuffer, index, size, setting.value.boolean);
break;
case NumberSetting:
index = unpackDouble(pBuffer, index, size, setting.value.number);
break;
default:
index = 0;
}
return index;
}
static void tensorDiag(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
int k = unpackInteger(raw_message);
finalize(raw_message);
r->diag(*t, k);
}
static void tensorIndexFill(rpc::RPCMessage& raw_message) {
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
int dim = unpackInteger(raw_message);
thpp::Tensor *index = unpackRetrieveTensor(raw_message);
thpp::Type type = peekType(raw_message);
if (thpp::isInteger(type)) {
auto val = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(tensor)->indexFill(dim, *index, val);
} else if (thpp::isFloat(type)) {
auto val = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(tensor)->indexFill(dim, *index, val);
} else {
throw std::runtime_error("expected a scalar type");
}
}
static void tensorIndexAdd(rpc::RPCMessage& raw_message) {
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
int dim = unpackInteger(raw_message);
thpp::Tensor *index = unpackRetrieveTensor(raw_message);
thpp::Tensor *src = unpackRetrieveTensor(raw_message);
finalize(raw_message);
tensor->indexAdd(dim, *index, *src);
}
static void tensorNorm(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
int dimension = unpackInteger(raw_message);
int keepdim = unpackInteger(raw_message);
if (thpp::isInteger(r->type())) {
long long value = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(r)->norm(*t, value, dimension, keepdim);
} else if (thpp::isFloat(r->type())) {
double value = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(r)->norm(*t, value, dimension, keepdim);
} else {
throw std::runtime_error("expected scalar type");
}
}
static void tensorLogspace(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
long n = unpackInteger(raw_message);
if (thpp::isInteger(r->type())) {
long long a = unpackInteger(raw_message);
long long b = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(r)->logspace(a, b, n);
} else if (thpp::isFloat(r->type())) {
double a = unpackFloat(raw_message);
double b = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(r)->logspace(a, b, n);
} else {
throw std::invalid_argument("expected scalar type");
}
}
static void tensorBhistc(rpc::RPCMessage& raw_message) {
thpp::Tensor *hist = unpackRetrieveTensor(raw_message);
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
long nbins = unpackInteger(raw_message);
if (thpp::isInteger(hist->type())) {
long long minvalue = unpackInteger(raw_message);
long long maxvalue = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(hist)->bhistc(*tensor, nbins, minvalue, maxvalue);
} else if (thpp::isFloat(hist->type())) {
double minvalue = unpackFloat(raw_message);
double maxvalue = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(hist)->bhistc(*tensor, nbins, minvalue, maxvalue);
} else {
throw std::invalid_argument("expected scalar type");
}
}
static void tensorRange(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Type type = peekType(raw_message);
if (thpp::isInteger(type)) {
long long xmin = unpackInteger(raw_message);
long long xmax = unpackInteger(raw_message);
long long step = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(r)->range(xmin, xmax, step);
} else if (thpp::isFloat(type)) {
double xmin = unpackFloat(raw_message);
double xmax = unpackFloat(raw_message);
double step = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(r)->range(xmin, xmax, step);
} else {
throw std::runtime_error("expected a scalar type");
}
}
static void tensorRenorm(rpc::RPCMessage& raw_message) {
thpp::Tensor *res = unpackRetrieveTensor(raw_message);
thpp::Tensor *src = unpackRetrieveTensor(raw_message);
int dimension = unpackInteger(raw_message);
if (thpp::isInteger(res->type())) {
long long value = unpackInteger(raw_message);
long long maxnorm = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(res)->renorm(*src, value, dimension, maxnorm);
} else if (thpp::isFloat(res->type())) {
double value = unpackFloat(raw_message);
double maxnorm = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(res)->renorm(*src, value, dimension, maxnorm);
} else {
throw std::invalid_argument("expected scalar type");
}
}
static void tensorFill(rpc::RPCMessage& raw_message) {
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
thpp::Type type = peekType(raw_message);
if (thpp::isInteger(type)) {
auto value = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(t)->fill(value);
} else if (thpp::isFloat(type)) {
auto value = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(t)->fill(value);
} else {
throw std::runtime_error("expected a scalar type");
}
}
static void tensorStdall(rpc::RPCMessage& raw_message) {
thpp::Tensor *tensor = unpackRetrieveTensor(raw_message);
int biased = unpackInteger(raw_message);
finalize(raw_message);
if (thpp::isInteger(tensor->type())) {
long long response = dynamic_cast<thpp::IntTensor*>(tensor)->stdall(biased);
sendValueToMaster(response);
} else if (thpp::isFloat(tensor->type())) {
double response = dynamic_cast<thpp::FloatTensor*>(tensor)->stdall(biased);
sendValueToMaster(response);
} else {
throw std::invalid_argument("expected scalar type");
}
}
static void tensorTpow(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
thpp::Tensor *t = unpackRetrieveTensor(raw_message);
if (thpp::isInteger(r->type())) {
long long value = unpackInteger(raw_message);
finalize(raw_message);
dynamic_cast<thpp::IntTensor*>(r)->tpow(value, *t);
} else if (thpp::isFloat(t->type())) {
double value = unpackFloat(raw_message);
finalize(raw_message);
dynamic_cast<thpp::FloatTensor*>(r)->tpow(value, *t);
} else {
throw std::runtime_error("expected a scalar type");
}
}
static void tensorNormall(rpc::RPCMessage& raw_message) {
thpp::Tensor *r = unpackRetrieveTensor(raw_message);
if (thpp::isInteger(r->type())) {
long long value = unpackInteger(raw_message);
finalize(raw_message);
long long response = dynamic_cast<thpp::IntTensor*>(r)->normall(value);
sendValueToMaster(response);
} else if (thpp::isFloat(r->type())) {
double value = unpackFloat(raw_message);
finalize(raw_message);
double response = dynamic_cast<thpp::FloatTensor*>(r)->normall(value);
sendValueToMaster(response);
} else {
throw std::invalid_argument("expected scalar type");
}
}
