Yurii Shyrma 5d9b2a16e5 Shyrma temp (#131)
* - specifying template instantiation for certain types in float16 and bloat16

Signed-off-by: Yurii <iuriish@yahoo.com>

* - polishing bfloat16 and float16 member functions template specialization

Signed-off-by: Yurii <iuriish@yahoo.com>

* - rewrite and overload array +-*/ scalar and scalar +-*/ arr in NDAray class

Signed-off-by: Yurii <iuriish@yahoo.com>

* - make corrections which have to do with and rvalue lvalue conversions

Signed-off-by: Yurii <iuriish@yahoo.com>

* - provide move semantic in NDArray operators array +-/* array

Signed-off-by: Yurii <iuriish@yahoo.com>

* float16/bfloat16 tweaks

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

* one more tweak

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

* - make float16 and bfloat16 to compile successfully on cuda

Signed-off-by: Yurii <iuriish@yahoo.com>

* - do not use resources of view-like arrays when move semantics is applied

Signed-off-by: Yurii <iuriish@yahoo.com>

* - get rid of pointers in signatures NDArray methods 1

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correction of signature of NDArray::dup method

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correction of signature of NDArray::reduceAlongDimension method

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyIndexReduce and applyTrueBroadcast methods

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyReduce3 and varianceAlongDimension methods

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::tensorsAlongDimension and diagonal methods

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::allTensorsAlongDimension

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::reduceAlongDimension 2

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyTransform 2

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyPairwiseTransform 2

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyBroadcast 2

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyTrueBroadcast 2

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::applyScalar and applyScalarArr

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::lambda methods

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::reduce3 methods 2

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of following NDArray methods: add/sub/mul/div row/column and fillAsTriangular

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::tileToShape methods

Signed-off-by: Yurii <iuriish@yahoo.com>

* - signature correction of NDArray::isShapeSameStrict method

Signed-off-by: Yurii <iuriish@yahoo.com>

* minor corrections in tests

Signed-off-by: Yurii <iuriish@yahoo.com>

* - replace reduce op in batchnorm mkldnn

Signed-off-by: Yurii <iuriish@yahoo.com>

* - add explicit templates instantiations for operator+(NDArray&&. const scalar)

Signed-off-by: Yurii <iuriish@yahoo.com>

* - corrections of casts in float16/bfloat16

Signed-off-by: Yurii <iuriish@yahoo.com>

* - provide move semantics in following NDArray methods: transform, applyTrueBroadcast, transpose, reshape, permute

Signed-off-by: Yurii <iuriish@yahoo.com>

* - get rid of input array A duplicate in svd cuda op

Signed-off-by: Yurii <iuriish@yahoo.com>

* - avoid available bug in svd cuda API

Signed-off-by: Yurii <iuriish@yahoo.com>

* - add temporary global memory buffer in svd cuda when calcUV = false and  m != n

Signed-off-by: Yurii <iuriish@yahoo.com>

* - remove test with blfoat16 type for betainC

Signed-off-by: Yurii <iuriish@yahoo.com>

* - resolve conflicts after master has been merged in

Signed-off-by: Yurii <iuriish@yahoo.com>

* - changed type of affected input array in fused_batch_norm

Signed-off-by: Yurii <iuriish@yahoo.com>

* - add several explicit type castings

Signed-off-by: Yurii <iuriish@yahoo.com>

* - add ND4J_EXPORT to operators

Signed-off-by: Yurii <iuriish@yahoo.com>

* - add explicit template types in instantiations of template arithm operators of NDArray class

Signed-off-by: Yurii <iuriish@yahoo.com>

* - one more test fix

Signed-off-by: Yurii <iuriish@yahoo.com>

Co-authored-by: raver119 <raver119@gmail.com>
2019-12-20 22:35:39 +03:00

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/*******************************************************************************
* 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 Yurii Shyrma (iuriish@yahoo.com), created on 17.05.2018
// @author raver119@gmail.com
//
#include <ops/declarable/helpers/percentile.h>
#include <NDArrayFactory.h>
#include <helpers/ConstantTadHelper.h>
#include <helpers/DebugHelper.h>
#include "ResultSet.h"
namespace nd4j {
namespace ops {
namespace helpers {
template <typename X>
static _CUDA_G void percentileKernel(void *vx, Nd4jLong *xTadShapeInfo, Nd4jLong *xTadOffsets, const Nd4jLong numTads, const Nd4jLong tadLength, void *vz, Nd4jLong *zShapeInfo, const Nd4jLong zLength, const Nd4jLong position) {
for (int t = blockIdx.x; t < numTads; t += gridDim.x) {
auto x = reinterpret_cast<X*>(vx) + xTadOffsets[t];
auto z = reinterpret_cast<X*>(vz);
// sort tad
if (tadLength > 1) {
for (int m = 0; m < tadLength; m++) {
if (m % 2 == 0) {
for (int tid = threadIdx.x; tid < tadLength; tid += blockDim.x) {
auto top = 2 * tid + 1;
if (top < tadLength) {
auto t0 = shape::getIndexOffset(top - 1, xTadShapeInfo);
auto t1 = shape::getIndexOffset(top, xTadShapeInfo);
if (x[t0] > x[t1]) {
//swap values
X dz0 = x[t0];
x[t0] = x[t1];
x[t1] = dz0;
}
}
}
} else {
for (int tid = threadIdx.x; tid < tadLength; tid += blockDim.x) {
auto top = 2 * tid + 2;
if (top < tadLength) {
auto t0 = shape::getIndexOffset(top - 1, xTadShapeInfo);
auto t1 = shape::getIndexOffset(top, xTadShapeInfo);
if (x[t0] > x[t1]) {
//swap values
X dz0 = x[t0];
x[t0] = x[t1];
x[t1] = dz0;
}
}
}
}
__syncthreads();
}
}
// saving final value
if (threadIdx.x == 0)
z[shape::getIndexOffset(t, zShapeInfo)] = x[shape::getIndexOffset(position, xTadShapeInfo)];
__syncthreads();
}
}
template <typename T>
static void _percentile(nd4j::LaunchContext * context, const NDArray& input, NDArray& output, std::vector<int>& axis, const float q, const int interpolation) {
const int inputRank = input.rankOf();
if(axis.empty())
for(int i=0; i<inputRank; ++i)
axis.push_back(i);
else
shape::checkDimensions(inputRank, axis);
auto tempArray = input.dup(input.ordering());
auto packX = ConstantTadHelper::getInstance()->tadForDimensions(tempArray.getShapeInfo(), axis);
auto tadLength = shape::length(packX.primaryShapeInfo());
const float fraction = 1.f - q / 100.;
Nd4jLong position = 0;
switch(interpolation) {
case 0: // lower
position = static_cast<Nd4jLong>(math::nd4j_ceil<float,T>((tadLength - 1) * fraction));
break;
case 1: // higher
position = static_cast<Nd4jLong>(math::nd4j_floor<float,T>((tadLength - 1) * fraction));
break;
case 2: // nearest
position = static_cast<Nd4jLong>(math::nd4j_round<float,T>((tadLength - 1) * fraction));
break;
}
position = tadLength - position - 1;
percentileKernel<T><<<256, 512, 1024, *context->getCudaStream()>>>(tempArray.specialBuffer(), packX.platformShapeInfo(), packX.platformOffsets(), packX.numberOfTads(), tadLength, output.specialBuffer(), output.specialShapeInfo(), output.lengthOf(), position);
nd4j::DebugHelper::checkErrorCode(context->getCudaStream(), "percentile");
}
void percentile(nd4j::LaunchContext * context, const NDArray& input, NDArray& output, std::vector<int>& axises, const float q, const int interpolation) {
NDArray::prepareSpecialUse({&output}, {&input});
BUILD_SINGLE_SELECTOR(input.dataType(), _percentile, (context, input, output, axises, q, interpolation), LIBND4J_TYPES);
NDArray::registerSpecialUse({&output}, {&input});
}
BUILD_SINGLE_TEMPLATE(template void _percentile, (nd4j::LaunchContext * context, const NDArray& input, NDArray& output, std::vector<int>& axises, const float q, const int interpolation), LIBND4J_TYPES);
}
}
}