* initial commit * additional data types & tensor type Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * missing include * sparse_to_dense Signed-off-by: raver119 <raver119@gmail.com> * few more tests files Signed-off-by: raver119 <raver119@gmail.com> * draft Signed-off-by: raver119 <raver119@gmail.com> * numeric sparse_to_dense Signed-off-by: raver119 <raver119@gmail.com> * comment Signed-off-by: raver119 <raver119@gmail.com> * string sparse_to_dense version Signed-off-by: raver119 <raver119@gmail.com> * CUDA DataBuffer expand Signed-off-by: raver119 <raver119@gmail.com> * few tweaks for CUDA build Signed-off-by: raver119 <raver119@gmail.com> * shape fn for string_split Signed-off-by: raver119 <raver119@gmail.com> * one more comment Signed-off-by: raver119 <raver119@gmail.com> * string_split indices Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * test passes Signed-off-by: raver119 <raver119@gmail.com> * few rearrangements for databuffer implementations Signed-off-by: raver119 <raver119@gmail.com> * DataBuffer: move inline methods to common implementations Signed-off-by: raver119 <raver119@gmail.com> * add native DataBuffer to Nd4j presets Signed-off-by: raver119 <raver119@gmail.com> * DataBuffer creation Signed-off-by: raver119 <raver119@gmail.com> * use DataBuffer for allocation Signed-off-by: raver119 <raver119@gmail.com> * cpu databuffer as deallocatable Signed-off-by: raver119 <raver119@gmail.com> * DataBuffer setters for bufers Signed-off-by: raver119 <raver119@gmail.com> * couple of wrappers Signed-off-by: raver119 <raver119@gmail.com> * DataBuffers being passed around Signed-off-by: raver119 <raver119@gmail.com> * Bunch of ByteBuffer-related signatures gone Signed-off-by: raver119 <raver119@gmail.com> * - few more Nd4j signatures removed - minor fix for bfloat16 Signed-off-by: raver119 <raver119@gmail.com> * nullptr pointer is still a pointer, but 0 as address :) Signed-off-by: raver119 <raver119@gmail.com> * one special test Signed-off-by: raver119 <raver119@gmail.com> * empty string array init Signed-off-by: raver119 <raver119@gmail.com> * one more test in cpp Signed-off-by: raver119 <raver119@gmail.com> * memcpy instead of databuffer swap Signed-off-by: raver119 <raver119@gmail.com> * special InteropDataBuffer for front-end languages Signed-off-by: raver119 <raver119@gmail.com> * few tweaks for java Signed-off-by: raver119 <raver119@gmail.com> * pointer/indexer actualization Signed-off-by: raver119 <raver119@gmail.com> * CustomOp returns list for inputArumgents and outputArguments instead of array Signed-off-by: raver119 <raver119@gmail.com> * redundant call Signed-off-by: raver119 <raver119@gmail.com> * print_variable op Signed-off-by: raver119 <raver119@gmail.com> * - view handling (but wrong one) - print_variable java wrapper Signed-off-by: raver119 <raver119@gmail.com> * one more test Signed-off-by: raver119 <raver119@gmail.com> * - empty arrays handling Signed-off-by: raver119 <raver119@gmail.com> * - deserialization works now Signed-off-by: raver119 <raver119@gmail.com> * minor fix Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * one more fix Signed-off-by: raver119 <raver119@gmail.com> * initial cuda commit Signed-off-by: raver119 <raver119@gmail.com> * print_variable message validation Signed-off-by: raver119 <raver119@gmail.com> * CUDA views Signed-off-by: raver119 <raver119@gmail.com> * CUDA special buffer size Signed-off-by: raver119 <raver119@gmail.com> * minor update to match master changes Signed-off-by: raver119 <raver119@gmail.com> * - consider arrays always actual on device for CUDA - additional PrintVariable constructor - CudaUtf8Buffer now allocates host buffer by default Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * - print_variable now allows print from device Signed-off-by: raver119 <raver119@gmail.com> * InteropDataBuffer data type fix Signed-off-by: raver119 <raver119@gmail.com> * ... Signed-off-by: raver119 <raver119@gmail.com> * disable some debug messages Signed-off-by: raver119 <raver119@gmail.com> * master pulled in Signed-off-by: raver119 <raver119@gmail.com> * couple of new methods for DataBuffer interop Signed-off-by: raver119 <raver119@gmail.com> * java side Signed-off-by: raver119 <raver119@gmail.com> * offsetted constructor Signed-off-by: raver119 <raver119@gmail.com> * new CUDA deallocator Signed-off-by: raver119 <raver119@gmail.com> * CUDA backend torn apart Signed-off-by: raver119 <raver119@gmail.com> * CUDA backend torn apart 2 Signed-off-by: raver119 <raver119@gmail.com> * CUDA backend torn apart 3 Signed-off-by: raver119 <raver119@gmail.com> * - few new tests - few new methods for DataBuffer management Signed-off-by: raver119 <raver119@gmail.com> * few more tests + few more tweaks Signed-off-by: raver119 <raver119@gmail.com> * two failing tests Signed-off-by: raver119 <raver119@gmail.com> * one more test Signed-off-by: raver119 <raver119@gmail.com> * two failing tests pass Signed-off-by: raver119 <raver119@gmail.com> * now we pass DataBuffer to legacy ops too Signed-off-by: raver119 <raver119@gmail.com> * Native DataBuffer for legacy ops, Java side Signed-off-by: raver119 <raver119@gmail.com> * CPU java side update Signed-off-by: raver119 <raver119@gmail.com> * CUDA java side update Signed-off-by: raver119 <raver119@gmail.com> * no more prepare/register action on java side Signed-off-by: raver119 <raver119@gmail.com> * NDArray::prepare/register use now accepts vectors Signed-off-by: raver119 <raver119@gmail.com> * InteropDataBuffer now has few more convenience methods Signed-off-by: raver119 <raver119@gmail.com> * java bindings update Signed-off-by: raver119 <raver119@gmail.com> * tick device in NativeOps Signed-off-by: raver119 <raver119@gmail.com> * Corrected usage of OpaqueBuffer for tests. * Corrected usage of OpaqueBuffer for java tests. * NativeOpsTests fixes. * print_variable now returns scalar Signed-off-by: raver119 <raver119@gmail.com> * one more test Signed-off-by: raver119 <raver119@gmail.com> * compat_string_split fix for CUDA Signed-off-by: raver119 <raver119@gmail.com> * - CUDA execScalar fix - CUDA lazyAllocateHostPointer now checks java indexer/pointer instead of native pointer Signed-off-by: raver119 <raver119@gmail.com> * legacy ops DataBuffer migration prototype Signed-off-by: raver119 <raver119@gmail.com> * ignore device shapeinfo coming from java Signed-off-by: raver119 <raver119@gmail.com> * minor fix Signed-off-by: raver119 <raver119@gmail.com> * minor transformAny fix Signed-off-by: raver119 <raver119@gmail.com> * minor tweak for lazy host allocation Signed-off-by: raver119 <raver119@gmail.com> * - DataBuffer::memcpy method - bitcast now uses memcpy Signed-off-by: raver119 <raver119@gmail.com> * - IndexReduce CUDA dimension buffer fix Signed-off-by: raver119 <raver119@gmail.com> * views for CPU and CUDA Signed-off-by: raver119 <raver119@gmail.com> * less spam Signed-off-by: raver119 <raver119@gmail.com> * optional memory init Signed-off-by: raver119 <raver119@gmail.com> * async memset Signed-off-by: raver119 <raver119@gmail.com> * - SummaryStats CUDA fix - DataBuffer.sameUnderlyingData() impl - execBroadcast fix Signed-off-by: raver119 <raver119@gmail.com> * - reduce3All fix switch to CUDA 10 temporarily Signed-off-by: raver119 <raver119@gmail.com> * CUDA version Signed-off-by: raver119 <raver119@gmail.com> * proper memory deallocator registration Signed-off-by: raver119 <raver119@gmail.com> * HOST_ONLY workspace allocation Signed-off-by: raver119 <raver119@gmail.com> * temp commit Signed-off-by: raver119 <raver119@gmail.com> * few conflicts resolved Signed-off-by: raver119 <raver119@gmail.com> * few minor fixes Signed-off-by: raver119 <raver119@gmail.com> * one more minor fix Signed-off-by: raver119 <raver119@gmail.com> * NDArray permute should operate on JVM primitives Signed-off-by: raver119 <raver119@gmail.com> * - create InteropDataBuffer for shapes as well - update pointers after view creation in Java Signed-off-by: raver119 <raver119@gmail.com> * - addressPointer temporary moved to C++ Signed-off-by: raver119 <raver119@gmail.com> * CUDA: don't account offset twice Signed-off-by: raver119 <raver119@gmail.com> * CUDA: DataBuffer pointer constructor updated Signed-off-by: raver119 <raver119@gmail.com> * CUDA NDArray.unsafeDuplication() simplified Signed-off-by: raver119 <raver119@gmail.com> * CUDA minor workspace-related fixes Signed-off-by: raver119 <raver119@gmail.com> * CPU DataBuffer.reallocate() Signed-off-by: raver119 <raver119@gmail.com> * print_affinity op Signed-off-by: raver119 <raver119@gmail.com> * print_affinity java side Signed-off-by: raver119 <raver119@gmail.com> * CUDA more tweaks for data locality Signed-off-by: raver119 <raver119@gmail.com> * - compat_string_split tweak - CudaUtf8Buffer update Signed-off-by: raver119 <raver119@gmail.com> * INDArray.close() mechanic restored Signed-off-by: raver119 <raver119@gmail.com> * one more test fixed Signed-off-by: raver119 <raver119@gmail.com> * - CUDA DataBuffer.reallocate() updated - cudaMemcpy (synchronous) restored Signed-off-by: raver119 <raver119@gmail.com> * one last fix Signed-off-by: raver119 <raver119@gmail.com> * bad import removed Signed-off-by: raver119 <raver119@gmail.com> * another small fix Signed-off-by: raver119 <raver119@gmail.com> * one special test Signed-off-by: raver119 <raver119@gmail.com> * fix bad databuffer size Signed-off-by: raver119 <raver119@gmail.com> * release primaryBuffer on replace Signed-off-by: raver119 <raver119@gmail.com> * higher timeout Signed-off-by: raver119 <raver119@gmail.com> * disable timeouts Signed-off-by: raver119 <raver119@gmail.com> * dbCreateView now validates offset and length of a view Signed-off-by: raver119 <raver119@gmail.com> * additional validation for dbExpand Signed-off-by: raver119 <raver119@gmail.com> * restore timeout back again Signed-off-by: raver119 <raver119@gmail.com> * smaller distribution for rng test to prevent timeouts Signed-off-by: raver119 <raver119@gmail.com> * CUDA DataBuffer::memcpy now copies to device all the time Signed-off-by: raver119 <raver119@gmail.com> * OpaqueDataBuffer now contains all required methods for interop Signed-off-by: raver119 <raver119@gmail.com> * some javadoc Signed-off-by: raver119 <raver119@gmail.com> * GC on failed allocations Signed-off-by: raver119 <raver119@gmail.com> * minoe memcpu tweak Signed-off-by: raver119 <raver119@gmail.com> * one more bitcast test Signed-off-by: raver119 <raver119@gmail.com> * - NDArray::deviceId() propagation - special multi-threaded test for data locality checks Signed-off-by: raver119 <raver119@gmail.com> * DataBuffer additional syncStream Signed-off-by: raver119 <raver119@gmail.com> * DataBuffer additional syncStream Signed-off-by: raver119 <raver119@gmail.com> * one ignored test Signed-off-by: raver119 <raver119@gmail.com> * skip host alloc for empty arrays Signed-off-by: raver119 <raver119@gmail.com> * ByteBuffer support is back Signed-off-by: raver119 <raver119@gmail.com> * DataBuffer::memcpy minor fix Signed-off-by: raver119 <raver119@gmail.com> * few minor prelu/bp tweaks Signed-off-by: raver119 <raver119@gmail.com> * nullify-related fixes Signed-off-by: raver119 <raver119@gmail.com> * PReLU fixes (#157) Signed-off-by: Alex Black <blacka101@gmail.com> * Build fixed * Fix tests * one more ByteBuffer signature restored Signed-off-by: raver119 <raver119@gmail.com> * nd4j-jdbc-hsql profiles fix Signed-off-by: raver119 <raver119@gmail.com> * nd4j-jdbc-hsql profiles fix Signed-off-by: raver119 <raver119@gmail.com> * PReLU weight init fix Signed-off-by: Alex Black <blacka101@gmail.com> * Small PReLU fix Signed-off-by: Alex Black <blacka101@gmail.com> * - INDArray.migrate() reactivated - DataBuffer::setDeviceId(...) added - InteropDataBuffer Z syncToDevice added for views Signed-off-by: raver119 <raver119@gmail.com> * missed file Signed-off-by: raver119 <raver119@gmail.com> * Small tweak Signed-off-by: Alex Black <blacka101@gmail.com> * cuda 10.2 Signed-off-by: raver119 <raver119@gmail.com> * minor fix Signed-off-by: raver119 <raver119@gmail.com> Co-authored-by: shugeo <sgazeos@gmail.com> Co-authored-by: Alex Black <blacka101@gmail.com> Co-authored-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
537 lines
18 KiB
C++
537 lines
18 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author raver119@gmail.com
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//
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#include <Context.h>
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#include <helpers/ShapeUtils.h>
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#include <graph/Context.h>
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#include <array/InteropDataBuffer.h>
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namespace nd4j {
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namespace graph {
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Context::Context(ContextPrototype* prototype, VariableSpace* variableSpace) {
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_variableSpace = variableSpace;
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_dataType = prototype->dataType();
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if (prototype != nullptr) {
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for (const auto &v: *(prototype->inputs())) {
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this->_inputs.push_back(v);
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}
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for (const auto &v: *(prototype->getTArguments())) {
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this->_tArgs.push_back(v);
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}
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for (const auto &v: *(prototype->getIArguments())) {
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this->_iArgs.push_back(v);
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}
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for (const auto &v: *(prototype->getBArguments())) {
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this->_bArgs.push_back(v);
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}
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for (const auto &v: *(prototype->getAxis())) {
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this->_axis.push_back(v);
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}
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this->_opNum = prototype->opNum();
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this->_isInplace = prototype->isInplace();
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this->_nodeId = prototype->nodeId();
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this->_useMKLDNN = prototype->isUseMKLDNN();
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}
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if (variableSpace != nullptr && variableSpace->launchContext()->getWorkspace() != nullptr)
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this->_workspace = variableSpace->launchContext()->getWorkspace();
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}
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nd4j::DataType Context::dataType(int index) {
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return _dataType;
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}
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nd4j::DataType Context::dataType() {
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return dataType(0);
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}
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void Context::setDataType(int index, nd4j::DataType type) {
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if (this->_dataTypes.size() > (size_t)index)
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_dataTypes[index] = type;
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_dataType = type;
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}
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Context::Context(int nodeId, VariableSpace *variableSpace) {
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this->_nodeId = nodeId;
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this->_variableSpace = variableSpace;
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this->_isInplace = false;
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this->_workspace = nullptr;
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this->_executionTime.first = 0;
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this->_executionTime.second = 0;
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if (variableSpace != nullptr && variableSpace->launchContext()->getWorkspace() != nullptr)
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this->_workspace = variableSpace->launchContext()->getWorkspace();
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}
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Context::Context(int nodeId, VariableSpace *variableSpace, bool isInplace) : Context(nodeId, variableSpace) {
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this->_isInplace = isInplace;
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}
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Context::~Context() {
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this->_iArgs.clear();
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this->_tArgs.clear();
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this->_inputs.clear();
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this->_fastpath_in.clear();
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this->_fastpath_out.clear();
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for (auto v:_handles)
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delete v;
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if (_context != nullptr)
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delete _context;
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}
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bool Context::hasWorkspaceProvided() {
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return this->_workspace != nullptr;
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}
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void Context::attachWorkspace(nd4j::memory::Workspace* workspace) {
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this->_workspace = workspace;
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}
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void Context::setVariableSpace(VariableSpace *variableSpace) {
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this->_variableSpace = variableSpace;
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}
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void Context::forgetWorkspace() {
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_workspace = nullptr;
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}
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std::vector<NDArray*>& Context::fastpath_in() {
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return _fastpath_in;
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}
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std::vector<NDArray*>& Context::fastpath_out() {
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return _fastpath_out;
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}
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bool Context::isFastPath() {
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return !(_fastpath_in.empty() && _fastpath_out.empty());
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}
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VariableSpace *Context::getVariableSpace() {
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return _variableSpace;
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}
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nd4j::memory::Workspace* Context::getWorkspace() {
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return _workspace;
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}
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nd4j::memory::Workspace* Context::workspace() {
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return _workspace;
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}
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nd4j::random::RandomBuffer* Context::getRNG() {
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return _rng;
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}
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void Context::setRNG(nd4j::random::RandomBuffer* rng) {
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_rng = rng;
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}
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/**
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* This method returns variableSpace used in this block
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* @return
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*/
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/*
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VariableSpace* Context::getVariableSpace() {
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return _variableSpace;
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}
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*/
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Stash* Context::getStash() {
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return _variableSpace->getStash();
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}
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void Context::trackList(NDArrayList* list) {
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_variableSpace->trackList(list);
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}
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/*
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void Block::updateVariables() {
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_variables.clear();
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auto x = _inputs.size();
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for (auto &v:_inputs) {
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auto var = _variableSpace->getVariable(v);
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_variables.emplace_back(var);
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}
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}
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*/
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int Context::getBranch() {
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return _variableSpace->flowPath()->branch(this->nodeId());
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}
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void Context::setBranch(int branch) {
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//_branch = branch;
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if (_variableSpace->flowPath() != nullptr)
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_variableSpace->flowPath()->markBranch(this->nodeId(), branch);
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}
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Nd4jLong nd4j::graph::Context::getOuterTime(){
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return this->_executionTime.first;
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}
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Nd4jLong nd4j::graph::Context::getInnerTime(){
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return this->_executionTime.second;
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}
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void nd4j::graph::Context::setOuterTime(Nd4jLong time){
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this->_executionTime.first = time;
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}
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void nd4j::graph::Context::setInnerTime(Nd4jLong time){
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this->_executionTime.second = time;
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}
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Variable* Context::getVariable(int idx) {
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if (idx >= this->_inputs.size()) {
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nd4j_printf("Node %i; Variable [%i] requested, but only %i inputs available\n", this->_nodeId, idx, this->_inputs.size());
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throw std::runtime_error("Context: bad Variable index");
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}
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auto p = this->_inputs[idx];
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auto v = variable(p);
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if (Environment::getInstance()->isDebugAndVerbose() && v != nullptr && v->getNDArray() != nullptr) {
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auto array = v->getNDArray();
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std::string shape_ = ShapeUtils::shapeAsString(array);
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auto type = DataTypeUtils::asString(array->dataType());
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float m = std::numeric_limits<float>::quiet_NaN();
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if (!array->isEmpty()) {
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auto values = array->asIndexedString(16);
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nd4j_printf("Debug info for node_%i input[%i]; shape: %s; ews: [%i]; order: [%i]; dtype: [%s]; first values: %s\n", this->_nodeId, idx, shape_.c_str(), array->ews(), array->ordering(), type.c_str(), values.c_str());
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} else {
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nd4j_printf("Debug info for node_%i input[%i]; shape: %s; ews: [%i]; order: [%i]; dtype: [%s]; mean value: [%f]\n", this->_nodeId, idx, shape_.c_str(), array->ews(), array->ordering(), type.c_str(), m);
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}
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}
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return v;
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}
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Variable* Context::variable(int idx) {
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return getVariable(idx);
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}
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Variable* Context::variable(std::initializer_list<int> p) {
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if (p.size() != 2)
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throw std::runtime_error("Variable address should have size of 2");
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// FIXME: lol
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std::vector<int> vec(p);
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std::pair<int, int> pair(vec[0], vec[1]);
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return variable(pair);
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}
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Variable* Context::variable(int node, int idx) {
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std::pair<int, int> pair(node, idx);
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return variable(pair);
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}
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Variable* Context::variable(std::pair<int,int>& p) {
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if (!_variableSpace->hasVariable(p)) {
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nd4j_printf("Node %i; Non-existent variable requested: [%i:%i]\n", this->_nodeId, p.first, p.second);
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throw std::runtime_error("Bad variable");
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}
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return _variableSpace->getVariable(p);
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}
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void Context::pushNDArrayToVariableSpace(int nodeId, int index, NDArray *array, bool removable) {
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std::pair<int,int> pair(nodeId, index);
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|
pushNDArrayToVariableSpace(pair, array, removable);
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|
}
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|
|
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void Context::pushNDArrayToVariableSpace(std::pair<int, int> &pair, NDArray *array, bool removable) {
|
|
if (_variableSpace != nullptr) {
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|
if (!_variableSpace->hasVariable(pair)) {
|
|
auto var = new Variable(array, nullptr, pair.first, pair.second);
|
|
_variableSpace->putVariable(pair, var);
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|
var->markRemovable(removable);
|
|
} else {
|
|
auto var = _variableSpace->getVariable(pair);
|
|
if (var->hasNDArray()) {
|
|
if (var->getNDArray() != array) {
|
|
if (var->isRemovable() && var->hasNDArray())
|
|
delete var->getNDArray();
|
|
|
|
var->setNDArray(array);
|
|
var->markRemovable(removable);
|
|
}
|
|
} else {
|
|
var->setNDArray(array);
|
|
var->markRemovable(removable);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void Context::pushNDArrayListToVariableSpace(int nodeId, int index, NDArrayList* list, bool track) {
|
|
std::pair<int,int> pair(nodeId, index);
|
|
pushNDArrayListToVariableSpace(pair, list, track);
|
|
}
|
|
|
|
void Context::pushNDArrayListToVariableSpace(std::pair<int, int>& pair, NDArrayList* list, bool track) {
|
|
if (!_variableSpace->hasVariable(pair)) {
|
|
auto var = new Variable(nullptr, nullptr, pair.first, pair.second);
|
|
var->setNDArrayList(list);
|
|
_variableSpace->putVariable(pair, var);
|
|
} else {
|
|
auto var = _variableSpace->getVariable(pair);
|
|
var->setNDArrayList(list);
|
|
}
|
|
|
|
if (track)
|
|
_variableSpace->trackList(list);
|
|
}
|
|
|
|
Variable* Context::ensureVariable(int idx) {
|
|
std::pair<int, int> pair(this->nodeId(), idx);
|
|
|
|
if (_variableSpace == nullptr)
|
|
throw std::runtime_error("Context::ensureVariable VariableSpace is NULL!");
|
|
|
|
if (!_variableSpace->hasVariable(pair)) {
|
|
auto var = new Variable(nullptr, nullptr, this->nodeId(), idx);
|
|
_variableSpace->putVariable(pair, var);
|
|
return var;
|
|
} else {
|
|
return _variableSpace->getVariable(pair);
|
|
}
|
|
}
|
|
|
|
bool Context::isValueAvailable(int idx) {
|
|
auto var = ensureVariable(idx);
|
|
|
|
if (var->variableType() == VariableType::NDARRAY) {
|
|
return var->hasNDArray();
|
|
} else if (var->variableType() == VariableType::ARRAY_LIST) {
|
|
return var->hasNDArrayList();
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
NDArray* Context::getNDArray(int idx) {
|
|
return array(idx);
|
|
}
|
|
|
|
NDArray* Context::array(int idx) {
|
|
// we check for fastpath first
|
|
if (!_fastpath_in.empty() && _fastpath_in.size() > idx) {
|
|
return _fastpath_in[idx];
|
|
}
|
|
|
|
// if no luck for fastpath - return whatever is available
|
|
return getVariable(idx)->getNDArray();
|
|
}
|
|
|
|
nd4j::memory::Workspace *Context::fWorkspace() {
|
|
return workspace();
|
|
}
|
|
|
|
nd4j::memory::Workspace *Context::tWorkspace() {
|
|
return nullptr;
|
|
}
|
|
|
|
nd4j::memory::Workspace *Context::oWorkspace() {
|
|
return nullptr;
|
|
}
|
|
|
|
LaunchContext* Context::launchContext() {
|
|
//FIXME: we need proper context to be shared here
|
|
if (_context == nullptr) {
|
|
return LaunchContext::defaultContext();
|
|
} else {
|
|
return _context;
|
|
}
|
|
}
|
|
|
|
unsigned long Context::width() {
|
|
if (!_fastpath_in.empty())
|
|
return _fastpath_in.size();
|
|
else
|
|
return _inputs.size();
|
|
}
|
|
|
|
void Context::setInputArray(int index, NDArray *array, bool removable) {
|
|
if (_fastpath_in.size() < index + 1)
|
|
_fastpath_in.resize(index+1);
|
|
|
|
_fastpath_in[index] = array;
|
|
if (removable)
|
|
_handles.emplace_back(array);
|
|
}
|
|
|
|
void Context::setInputArray(int index, void *buffer, void *shapeInfo, void *specialBuffer, void *specialShapeInfo) {
|
|
auto array = new NDArray(buffer, specialBuffer, reinterpret_cast<Nd4jLong *>(shapeInfo));
|
|
|
|
if (_fastpath_in.size() < index + 1)
|
|
_fastpath_in.resize(index+1);
|
|
|
|
_fastpath_in[index] = array;
|
|
_handles.emplace_back(array);
|
|
|
|
if (_context != nullptr)
|
|
array->setContext(_context);
|
|
}
|
|
|
|
void Context::setOutputArray(int index, NDArray *array, bool removable) {
|
|
if (_fastpath_out.size() < index + 1)
|
|
_fastpath_out.resize(index+1);
|
|
|
|
_fastpath_out[index] = array;
|
|
|
|
if (removable)
|
|
_handles.emplace_back(array);
|
|
}
|
|
|
|
void Context::setOutputArray(int index, void *buffer, void *shapeInfo, void *specialBuffer, void *specialShapeInfo) {
|
|
if (_fastpath_out.size() < index + 1)
|
|
_fastpath_out.resize(index+1);
|
|
|
|
auto array = new NDArray(buffer, specialBuffer, reinterpret_cast<Nd4jLong *>(shapeInfo));
|
|
|
|
_fastpath_out[index] = array;
|
|
_handles.emplace_back(array);
|
|
|
|
if (_context != nullptr)
|
|
array->setContext(_context);
|
|
}
|
|
|
|
void Context::setInputArray(int index, void *vdatabuffer, void *shapeInfo, void *specialShapeInfo) {
|
|
auto dataBuffer = reinterpret_cast<InteropDataBuffer*>(vdatabuffer);
|
|
|
|
if (_fastpath_in.size() < index + 1)
|
|
_fastpath_in.resize(index+1);
|
|
|
|
NDArray *array;
|
|
if (dataBuffer != nullptr)
|
|
array = new NDArray(dataBuffer->dataBuffer(), reinterpret_cast<Nd4jLong *>(shapeInfo), nd4j::LaunchContext::defaultContext(), dataBuffer->offset() / DataTypeUtils::sizeOf(ArrayOptions::dataType(reinterpret_cast<Nd4jLong *>(shapeInfo))));
|
|
else
|
|
array = new NDArray(nullptr, nullptr, reinterpret_cast<Nd4jLong *>(shapeInfo));
|
|
|
|
_fastpath_in[index] = array;
|
|
_handles.emplace_back(array);
|
|
|
|
if (_context != nullptr)
|
|
array->setContext(_context);
|
|
}
|
|
|
|
void Context::setOutputArray(int index, void *vdatabuffer, void *shapeInfo, void *specialShapeInfo) {
|
|
auto dataBuffer = reinterpret_cast<InteropDataBuffer*>(vdatabuffer);
|
|
|
|
if (_fastpath_out.size() < index + 1)
|
|
_fastpath_out.resize(index+1);
|
|
|
|
NDArray *array;
|
|
if (dataBuffer != nullptr)
|
|
array = new NDArray(dataBuffer->dataBuffer(), reinterpret_cast<Nd4jLong *>(shapeInfo), nd4j::LaunchContext::defaultContext(), dataBuffer->offset() / DataTypeUtils::sizeOf(ArrayOptions::dataType(reinterpret_cast<Nd4jLong *>(shapeInfo))));
|
|
else
|
|
array = new NDArray(nullptr, nullptr, reinterpret_cast<Nd4jLong *>(shapeInfo));
|
|
|
|
_fastpath_out[index] = array;
|
|
_handles.emplace_back(array);
|
|
|
|
if (_context != nullptr)
|
|
array->setContext(_context);
|
|
}
|
|
|
|
void Context::setTArguments(double *arguments, int numberOfArguments) {
|
|
_tArgs.clear();
|
|
_tArgs.reserve(numberOfArguments);
|
|
for (int e = 0; e < numberOfArguments; e++)
|
|
_tArgs.push_back(arguments[e]);
|
|
}
|
|
|
|
void Context::setIArguments(Nd4jLong *arguments, int numberOfArguments) {
|
|
_iArgs.clear();
|
|
_iArgs.reserve(numberOfArguments);
|
|
for (int e = 0; e < numberOfArguments; e++)
|
|
_iArgs.push_back(arguments[e]);
|
|
}
|
|
|
|
void Context::setBArguments(bool *arguments, int numberOfArguments) {
|
|
_bArgs.clear();
|
|
_bArgs.reserve(numberOfArguments);
|
|
for (int e = 0; e < numberOfArguments; e++)
|
|
_bArgs.push_back(arguments[e]);
|
|
}
|
|
|
|
void Context::setCudaContext(Nd4jPointer cudaStream, Nd4jPointer reductionPointer, Nd4jPointer allocationPointer) {
|
|
#ifdef __CUDABLAS__
|
|
_context = new LaunchContext(cudaStream, reductionPointer, allocationPointer);
|
|
|
|
// FIXME: either pass handle from outside, or make sure outside we use the same handle
|
|
_context->setCublasHandle(LaunchContext::defaultContext()->getCublasHandle());
|
|
|
|
for (auto v: _fastpath_out)
|
|
v->setContext(_context);
|
|
|
|
for (auto v: _fastpath_in)
|
|
v->setContext(_context);
|
|
#endif
|
|
}
|
|
|
|
void Context::allowHelpers(bool reallyAllow) {
|
|
_helpersAllowed = reallyAllow;
|
|
}
|
|
|
|
bool Context::helpersAllowed() {
|
|
return _helpersAllowed;
|
|
}
|
|
|
|
void Context::setTArguments(const std::vector<double> &tArgs) {
|
|
for (auto t:tArgs)
|
|
_tArgs.emplace_back(t);
|
|
}
|
|
|
|
void Context::setIArguments(const std::vector<Nd4jLong> &iArgs) {
|
|
for (auto i:iArgs)
|
|
_iArgs.emplace_back(i);
|
|
}
|
|
|
|
void Context::setBArguments(const std::vector<bool> &bArgs) {
|
|
for (auto b:bArgs)
|
|
_bArgs.push_back(b);
|
|
}
|
|
|
|
void Context::setShapeFunctionOverride(bool reallyOverride) {
|
|
_shapeFunctionOverride = reallyOverride;
|
|
}
|
|
|
|
bool Context::shapeFunctionOverride() {
|
|
return _shapeFunctionOverride;
|
|
}
|
|
}
|
|
}
|
|
|