std::vector< std::pair< std::string, tk::real > >
writeUnsMesh( const tk::Print& print,
const std::string& filename,
UnsMesh& mesh,
bool reorder )
// *****************************************************************************
// Write unstructured mesh to file
//! \param[in] print Pretty printer
//! \param[in] filename Filename to write mesh to
//! \param[in] mesh Unstructured mesh object to write from
//! \param[in] reorder Whether to also reorder mesh nodes
//! \return Vector of time stamps consisting of a timer label (a string), and a
//! time state (a tk::real in seconds) measuring the renumber and the mesh
//! write time
//! \author J. Bakosi
// *****************************************************************************
{
std::vector< std::pair< std::string, tk::real > > times;
tk::Timer t;
if (reorder) {
print.diagstart( "Reordering mesh nodes ..." );
auto& inpoel = mesh.tetinpoel();
const auto psup = tk::genPsup( inpoel, 4, tk::genEsup( inpoel, 4 ) );
std::vector< std::size_t > map, invmap;
std::tie( map, invmap ) = tk::renumber( psup );
tk::remap( inpoel, map );
print.diagend( "done" );
times.emplace_back( "Renumber mesh", t.dsec() );
t.zero();
}
print.diagstart( "Writing mesh to file ..." );
const auto meshtype = pickOutput( filename );
if (meshtype == MeshWriter::GMSH)
GmshMeshWriter( filename ).writeMesh( mesh );
else if (meshtype == MeshWriter::NETGEN)
NetgenMeshWriter( filename ).writeMesh( mesh );
else if (meshtype== MeshWriter::EXODUSII)
ExodusIIMeshWriter( filename, ExoWriter::CREATE ).writeMesh( mesh );
print.diagend( "done" );
times.emplace_back( "Write mesh to file", t.dsec() );
return times;
}
nd4j::graph::Node::Node(nd4j::ops::DeclarableOp *customOp, int id, std::initializer_list<int> input, std::initializer_list<int> output, std::initializer_list<int> dimensions, float scalar, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs) {
this->_opType = OpType_CUSTOM;
this->_id = id;
this->_opNum = customOp->getOpHash();
this->_extraParams = nullptr;
this->_dataType = nd4j::DataType::FLOAT32; // float as default
this->_dim = nullptr;
this->_customOp = customOp;
_hasExternalInputs = false;
_hasExternalOutputs = false;
_hasInternalInputs = false;
_hasInternalOutputs = false;
_scalar = scalar;
for (auto i: input)
pickInput(i);
for (auto o: output)
pickOutput(o);
if (dimensions.size() > 0) {
_dim = new int[dimensions.size()];
int cnt = 0;
for (auto d: dimensions) {
_dimensions.push_back(d);
_dim[cnt++] = d;
}
}
auto block = new ContextPrototype(this->getCustomOp()->getOpDescriptor(), this->id(), false);
for (auto v: dimensions)
block->getAxis()->emplace_back(v);
for (auto v: iArgs)
block->getIArguments()->emplace_back(v);
for (auto v: tArgs)
block->getTArguments()->emplace_back(v);
this->setContextPrototype(block);
}
nd4j::graph::Node::Node(OpType opType, int opNum, int id, std::initializer_list<int> input, std::initializer_list<int> output, std::initializer_list<int> dimensions, float scalar, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs) {
this->_opType = opType;
this->_id = id;
this->_opNum = opNum;
this->_extraParams = nullptr;
this->_dataType = nd4j::DataType::FLOAT32; // float as default
this->_dim = nullptr;
_hasExternalInputs = false;
_hasExternalOutputs = false;
_hasInternalInputs = false;
_hasInternalOutputs = false;
_scalar = scalar;
for (auto i: input)
pickInput(i);
for (auto o: output)
pickOutput(o);
if (dimensions.size() > 0) {
_dim = new int[dimensions.size()];
int cnt = 0;
for (auto d: dimensions) {
_dimensions.push_back(d);
_dim[cnt++] = d;
}
}
// these ops allow in-place execution by design
if (opType == OpType_TRANSFORM_SAME || opType == OpType_TRANSFORM_FLOAT || opType == OpType_TRANSFORM_STRICT || opType == OpType_TRANSFORM_BOOL || opType == OpType_SCALAR || opType == OpType_BROADCAST) {
if (_output.size() <= 1) {
_isInplace = true;
}
_opClass = OpClass_TRANSFORM;
} else if (opType == OpType_REDUCE_SAME || opType == OpType_REDUCE_FLOAT || opType == OpType_REDUCE_BOOL || opType == OpType_REDUCE_LONG || opType == OpType_SUMMARYSTATS) {
_opClass = OpClass_REDUCTION;
}
if (opType == OpType_BROADCAST ||
opType == OpType_BROADCAST_BOOL ||
opType == OpType_INDEX_REDUCE ||
opType == OpType_SUMMARYSTATS ||
opType == OpType_REDUCE_BOOL ||
opType == OpType_REDUCE_SAME ||
opType == OpType_REDUCE_FLOAT ||
opType == OpType_REDUCE_3 ||
opType == OpType_TRANSFORM_STRICT ||
opType == OpType_TRANSFORM_SAME ||
opType == OpType_TRANSFORM_FLOAT ||
opType == OpType_TRANSFORM_BOOL ||
opType == OpType_RANDOM ||
opType == OpType_PAIRWISE ||
opType == OpType_PAIRWISE_BOOL ||
opType == OpType_SCALAR_BOOL ||
opType == OpType_SCALAR) {
this->_isDeductable = true;
auto block = new ContextPrototype(nullptr, this->id(), false);
for (auto v: dimensions)
block->getAxis()->emplace_back(v);
for (auto v: iArgs)
block->getIArguments()->emplace_back(v);
for (auto v: tArgs)
block->getTArguments()->emplace_back(v);
this->setContextPrototype(block);
this->setCustomOp(Node::buildOpByType(opType, (int) input.size(), (int) block->getIArguments()->size(), (int) block->getTArguments()->size(), opNum, &_scalar));
block->setOpDescriptor(this->getCustomOp()->getOpDescriptor());
} else if (opType == OpType_CUSTOM) {
if (this->getCustomOp()) {
auto block = new ContextPrototype(this->getCustomOp()->getOpDescriptor(), this->id(), false);
for (auto v: dimensions)
block->getAxis()->emplace_back(v);
for (auto v: iArgs)
block->getIArguments()->emplace_back(v);
for (auto v: tArgs)
block->getTArguments()->emplace_back(v);
this->setContextPrototype(block);
} else throw std::runtime_error("wrong custom operation given");
}
};
void nd4j::graph::Node::pickOutputOnce(int outputId) {
std::pair<int, int> pair(outputId, 0);
if (std::find(_output.begin(), _output.end(), pair) == _output.end())
pickOutput(outputId);
}
