29e8e09db6
* 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> |
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|---|---|---|
| .github | ||
| arbiter | ||
| datavec | ||
| deeplearning4j | ||
| docs | ||
| gym-java-client | ||
| jumpy | ||
| libnd4j | ||
| nd4j | ||
| nd4s | ||
| pydatavec | ||
| pydl4j | ||
| rl4j | ||
| scalnet | ||
| .gitignore | ||
| CONTRIBUTING.md | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| change-cuda-versions.sh | ||
| change-scala-versions.sh | ||
| perform-release.sh | ||
| pom.xml | ||
README.md
Monorepo of Deeplearning4j
Welcome to the new monorepo of Deeplearning4j that contains the source code for all the following projects, in addition to the original repository of Deeplearning4j moved to deeplearning4j:
- https://github.com/eclipse/deeplearning4j/tree/master/libnd4j
- https://github.com/eclipse/deeplearning4j/tree/master/nd4j
- https://github.com/eclipse/deeplearning4j/tree/master/datavec
- https://github.com/eclipse/deeplearning4j/tree/master/arbiter
- https://github.com/eclipse/deeplearning4j/tree/master/nd4s
- https://github.com/eclipse/deeplearning4j/tree/master/gym-java-client
- https://github.com/eclipse/deeplearning4j/tree/master/rl4j
- https://github.com/eclipse/deeplearning4j/tree/master/scalnet
- https://github.com/eclipse/deeplearning4j/tree/master/pydl4j
- https://github.com/eclipse/deeplearning4j/tree/master/jumpy
- https://github.com/eclipse/deeplearning4j/tree/master/pydatavec
To build everything, we can use commands like
./change-cuda-versions.sh x.x
./change-scala-versions.sh 2.xx
./change-spark-versions.sh x
mvn clean install -Dmaven.test.skip -Dlibnd4j.cuda=x.x -Dlibnd4j.compute=xx
or
mvn -B -V -U clean install -pl '!jumpy,!pydatavec,!pydl4j' -Dlibnd4j.platform=linux-x86_64 -Dlibnd4j.chip=cuda -Dlibnd4j.cuda=9.2 -Dlibnd4j.compute=<your GPU CC> -Djavacpp.platform=linux-x86_64 -Dmaven.test.skip=true
An example of GPU "CC" or compute capability is 61 for Titan X Pascal.
Want some examples?
We have separate repository with various examples available: https://github.com/eclipse/deeplearning4j-examples
In the examples repo, you'll also find a tutorial series in Zeppelin: https://github.com/eclipse/deeplearning4j-examples/tree/master/tutorials