raver119 7abc574eeb
Snapshot update (#8194)
* fix double consumption of rng on cpu

Signed-off-by: raver119 <raver119@gmail.com>

* Shyrma docs (#222)

* - documenting and profiling matrix_set_diag cuda kernel

Signed-off-by: Yurii <yurii@skymind.io>

* - correct formula of pnorm pooling in cuda 2d/3d kernels
- remove helper matrix_diag which duplicates work of helper matrix_set_diag

Signed-off-by: Yurii <yurii@skymind.io>

* cublasHandle sharing + lock

Signed-off-by: raver119 <raver119@gmail.com>

* cublasHandle sharing + lock

Signed-off-by: raver119 <raver119@gmail.com>

* Documentation from serialization/deserialization in NLP (#221)

* refactoring

Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>

* Javadocs

Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>

* Javadoc fixed

Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>

* Cleanup

Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>

* dedicated lock for getCudaCublasHandle

Signed-off-by: raver119 <raver119@gmail.com>

* Small fixes (#223)

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* ELU DL4J fixes (#224)

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* javadoc (#225)

Signed-off-by: Robert Altena <Rob@Ra-ai.com>

* Small test compilation fix (#226)

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* #8182 remove spark version suffix (#227)

Signed-off-by: AlexDBlack <blacka101@gmail.com>

* [WIP] Thread safety (#229)

* sync after cublas*gemm

Signed-off-by: raver119 <raver119@gmail.com>

* mutex for CublasHelper

Signed-off-by: raver119 <raver119@gmail.com>

* don't store cublasHandle in LaunchContext, it's per-device anyway

Signed-off-by: raver119 <raver119@gmail.com>

* some printout

Signed-off-by: raver119 <raver119@gmail.com>

* check for field instead

Signed-off-by: raver119 <raver119@gmail.com>

* pew-pew

Signed-off-by: raver119 <raver119@gmail.com>

* don't release ContextBuffers until device changed

Signed-off-by: raver119 <raver119@gmail.com>

* small tweak

Signed-off-by: raver119 <raver119@gmail.com>

* some logging in sgemm

Signed-off-by: raver119 <raver119@gmail.com>

* stream sync

Signed-off-by: raver119 <raver119@gmail.com>

* some more logging

Signed-off-by: raver119 <raver119@gmail.com>

* some more error checks

Signed-off-by: raver119 <raver119@gmail.com>

* one fancy test

Signed-off-by: raver119 <raver119@gmail.com>

* one fancy test

Signed-off-by: raver119 <raver119@gmail.com>

* minor AffinityManager fix

Signed-off-by: raver119 <raver119@gmail.com>

* cudaEvent error logging improvement

Signed-off-by: raver119 <raver119@gmail.com>

* ConstantHelper thread safety

Signed-off-by: raver119 <raver119@gmail.com>

* - minor corrections in ConstantTadHelper

Signed-off-by: Yurii <yurii@skymind.io>

* ConstantShapeHelper thread safety

Signed-off-by: raver119 <raver119@gmail.com>

* ConstantTadHelper.cu updated

Signed-off-by: raver119 <raver119@gmail.com>

* logging off

Signed-off-by: raver119 <raver119@gmail.com>

* logging off

Signed-off-by: raver119 <raver119@gmail.com>
2019-09-03 22:02:02 +03:00

274 lines
13 KiB
C++

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author raver119@gmail.com, created on 15.12.17.
// @author Yurii Shyrma (iuriish@yahoo.com)
//
#include <types/types.h>
#include <op_boilerplate.h>
#include <loops/random.h>
#include <OmpLaunchHelper.h>
using namespace randomOps;
namespace functions {
namespace random {
template<typename X>
template<typename OpClass>
void RandomFunction<X>::execTransform(Nd4jPointer state,
void *vx,
Nd4jLong *xShapeInfo,
void *vy,
Nd4jLong *yShapeInfo,
void *vz,
Nd4jLong *zShapeInfo,
void *vextraArguments) {
auto x = reinterpret_cast<X *>(vx);
auto y = reinterpret_cast<X *>(vy);
auto z = reinterpret_cast<X *>(vz);
auto extraArguments = reinterpret_cast<X *>(vextraArguments);
if (OpClass::requiresSpecial) {
OpClass::specialOp(state, x, xShapeInfo, y, yShapeInfo, z, zShapeInfo, extraArguments);
return;
}
auto length = shape::length(zShapeInfo);
// nd4j::random::RandomBuffer *buffer = reinterpret_cast<nd4j::random::RandomBuffer *> (state);
nd4j::graph::RandomGenerator* rng = reinterpret_cast<nd4j::graph::RandomGenerator*>(state);
nd4j::OmpLaunchHelper info(length);
if(shape::haveSameShapeAndStrides(xShapeInfo, yShapeInfo) && shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo)) {
uint xShapeInfoCast[MAX_RANK];
const bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto offset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
z[offset] = OpClass::op(x[offset], y[offset], i, length, rng, extraArguments);
}
}
}
else if (shape::haveSameShapeAndStrides(xShapeInfo, yShapeInfo)) {
uint xShapeInfoCast[MAX_RANK];
uint zShapeInfoCast[MAX_RANK];
const bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
const bool canCastZ = nd4j::DataTypeUtils::castShapeInfo(zShapeInfo, zShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto offset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
auto zOffset = shape::indexOffset(i + threadOffset, zShapeInfo, zShapeInfoCast, length, canCastZ);
z[zOffset] = OpClass::op(x[offset], y[offset], i, length, rng, extraArguments);
}
}
}
else if (shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo)) {
uint xShapeInfoCast[MAX_RANK];
uint yShapeInfoCast[MAX_RANK];
const bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
const bool canCastY = nd4j::DataTypeUtils::castShapeInfo(yShapeInfo, yShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto offset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
auto yOffset = shape::indexOffset(i + threadOffset, yShapeInfo, yShapeInfoCast, length, canCastY);
z[offset] = OpClass::op(x[offset], y[yOffset], i, length, rng, extraArguments);
}
}
}
else if (shape::haveSameShapeAndStrides(yShapeInfo, zShapeInfo)) {
uint xShapeInfoCast[MAX_RANK];
uint yShapeInfoCast[MAX_RANK];
const bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
const bool canCastY = nd4j::DataTypeUtils::castShapeInfo(yShapeInfo, yShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < info.getItersPerThread(threadNum); i++) {
auto xOffset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
auto offset = shape::indexOffset(i + threadOffset, yShapeInfo, yShapeInfoCast, length, canCastY);
z[offset] = OpClass::op(x[xOffset], y[offset], i, length, rng, extraArguments);
}
}
}
else {
uint xShapeInfoCast[MAX_RANK];
uint yShapeInfoCast[MAX_RANK];
uint zShapeInfoCast[MAX_RANK];
const bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
const bool canCastY = nd4j::DataTypeUtils::castShapeInfo(yShapeInfo, yShapeInfoCast);
const bool canCastZ = nd4j::DataTypeUtils::castShapeInfo(zShapeInfo, zShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto xOffset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
auto yOffset = shape::indexOffset(i + threadOffset, yShapeInfo, yShapeInfoCast, length, canCastY);
auto zOffset = shape::indexOffset(i + threadOffset, zShapeInfo, zShapeInfoCast, length, canCastZ);
z[zOffset] = OpClass::op(x[xOffset], y[yOffset], i, length, rng, extraArguments);
}
}
}
};
template<typename X>
template<typename OpClass>
void RandomFunction<X>::execTransform(Nd4jPointer state,
void *vx,
Nd4jLong *xShapeInfo,
void *vz,
Nd4jLong *zShapeInfo,
void *vextraArguments) {
auto x = reinterpret_cast<X *>(vx);
auto z = reinterpret_cast<X *>(vz);
auto extraArguments = reinterpret_cast<X *>(vextraArguments);
auto length = shape::length(zShapeInfo);
uint xShapeInfoCast[MAX_RANK];
const bool canCastX = nd4j::DataTypeUtils::castShapeInfo(xShapeInfo, xShapeInfoCast);
nd4j::graph::RandomGenerator* rng = reinterpret_cast<nd4j::graph::RandomGenerator*>(state);
nd4j::OmpLaunchHelper info(length);
if(shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo)) {
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto offset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
z[offset] = OpClass::op(x[offset], i, length, rng, extraArguments);
}
}
}
else {
uint zShapeInfoCast[MAX_RANK];
const bool canCastZ = nd4j::DataTypeUtils::castShapeInfo(zShapeInfo, zShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto xOffset = shape::indexOffset(i + threadOffset, xShapeInfo, xShapeInfoCast, length, canCastX);
auto zOffset = shape::indexOffset(i + threadOffset, zShapeInfo, zShapeInfoCast, length, canCastZ);
z[zOffset] = OpClass::op(x[xOffset], i, length, rng, extraArguments);
}
}
}
}
template<typename X>
template<typename OpClass>
void RandomFunction<X>::execTransform(Nd4jPointer state, void *vz, Nd4jLong *zShapeInfo, void *vextraArguments) {
auto z = reinterpret_cast<X *>(vz);
auto extraArguments = reinterpret_cast<X *>(vextraArguments);
auto length = shape::length(zShapeInfo);
//nd4j::random::RandomBuffer *buffer = reinterpret_cast<nd4j::random::RandomBuffer *> (state);
nd4j::graph::RandomGenerator* rng = reinterpret_cast<nd4j::graph::RandomGenerator*>(state);
nd4j::OmpLaunchHelper info(length);
uint zShapeInfoCast[MAX_RANK];
const bool canCastZ = nd4j::DataTypeUtils::castShapeInfo(zShapeInfo, zShapeInfoCast);
PRAGMA_OMP_PARALLEL_THREADS(info._numThreads)
{
auto threadNum = omp_get_thread_num();
auto threadOffset = info.getThreadOffset(threadNum);
auto ulen = static_cast<unsigned int>(info.getItersPerThread(threadNum));
PRAGMA_OMP_SIMD
for (Nd4jLong i = 0; i < ulen; i++) {
auto offset = shape::indexOffset(i + threadOffset, zShapeInfo, zShapeInfoCast, length, canCastZ);
z[offset] = OpClass::op(i+threadOffset, length, rng, extraArguments);
}
}
}
template<typename X>
void RandomFunction<X>::execTransform(int opNum, Nd4jPointer state, void *x, Nd4jLong *xShapeInfo, void *z, Nd4jLong *zShapeInfo, void *extraArguments) {
DISPATCH_BY_OPNUM_T(execTransform, PARAMS(state, x, xShapeInfo, z, zShapeInfo, extraArguments), RANDOM_OPS)
}
template<typename X>
void RandomFunction<X>::execTransform(int opNum, Nd4jPointer state, void *x, Nd4jLong *xShapeInfo, void *y, Nd4jLong *yShapeInfo, void *z, Nd4jLong *zShapeInfo, void *extraArguments) {
DISPATCH_BY_OPNUM_T(execTransform, PARAMS(state, x, xShapeInfo, y, yShapeInfo, z, zShapeInfo, extraArguments), RANDOM_OPS)
}
template<typename X>
void RandomFunction<X>::execTransform(int opNum, Nd4jPointer state, void *z, Nd4jLong *zShapeInfo, void *extraArguments) {
DISPATCH_BY_OPNUM_T(execTransform, PARAMS(state, z, zShapeInfo, extraArguments), RANDOM_OPS)
}
BUILD_SINGLE_TEMPLATE(template class ND4J_EXPORT RandomFunction, , FLOAT_TYPES);
}
}