cavis/libnd4j/include/ops/declarable/impl/LegacyStatsOp.cpp

119 lines
5.3 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
******************************************************************************/
//
// Created by raver119 on 17.10.2017.
//
#include <ops/declarable/LegacyStatsOp.h>
#include <helpers/ShapeUtils.h>
#include <helpers/TAD.h>
#include <helpers/ConstantTadHelper.h>
#include <array/DataTypeUtils.h>
namespace nd4j {
namespace ops {
Nd4jStatus LegacyStatsOp::validateAndExecute(Context &block) {
auto x = INPUT_VARIABLE(0);
auto z = OUTPUT_VARIABLE(0);
NDArray::prepareSpecialUse({z}, {x});
// we assume that opNuk is either stored in block, or was provided via op constructor
int opNum = block.opNum() < 0 ? this->_opNum : block.opNum();
// bias goes as first argument, unlike all other reductions
bool biasCorrected = false;
if (block.getIArguments()->size() > 0)
biasCorrected = INT_ARG(0) > 0;
ExtraArguments extras(*block.getTArguments());
PointersManager manager(block.launchContext(),"LegacyStatsOp");
if (block.getIArguments()->size() == 1 || (block.getIArguments()->size() == 2 && INT_ARG(1) == nd4j::DataTypeUtils::max<int>())) {
// scalar
NativeOpExecutioner::execSummaryStatsScalar(block.launchContext(), opNum, x->getBuffer(), x->getShapeInfo(), x->specialBuffer(), x->specialShapeInfo(),
extras.argumentsAsT(z->dataType()), z->getBuffer(), z->getShapeInfo(), z->specialBuffer(), z->specialShapeInfo(), biasCorrected);
} else {
// dimensions for TAD
// we should skip first argument here, because it's addressing bias correction
std::vector<int> dims(*block.getIArguments());
for (int e = 0; e < dims.size(); e++)
if (dims[e] < 0)
dims[e] += x->rankOf();
REQUIRE_TRUE(dims.size() > 0, 0, "Some dimensions requuired for reduction!");
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(x->getShapeInfo(), dims);
auto pTadShape = Environment::getInstance()->isCPU() ? packX.primaryShapeInfo() : packX.specialShapeInfo(); //(Nd4jLong *) manager.replicatePointer(tad.tadOnlyShapeInfo, shape::shapeInfoByteLength(tad.tadOnlyShapeInfo));
auto pTadOffsets = Environment::getInstance()->isCPU() ? packX.primaryOffsets() : packX.specialOffsets(); //(Nd4jLong *) manager.replicatePointer(tad.tadOffsets, tad.numTads * sizeof(Nd4jLong));
NativeOpExecutioner::execSummaryStats(block.launchContext(), opNum, x->getBuffer(), x->getShapeInfo(), x->specialBuffer(), x->specialShapeInfo(), extras.argumentsAsT(z->dataType()),
z->getBuffer(), z->getShapeInfo(), z->specialBuffer(), z->specialShapeInfo(), dims.data(), (int) dims.size(), pTadShape, pTadOffsets, biasCorrected);
}
manager.synchronize();
STORE_RESULT(*z);
return Status::OK();
}
LegacyStatsOp::LegacyStatsOp() : LegacyOp::LegacyOp(1) {
//
}
LegacyStatsOp::LegacyStatsOp(int opNum) : LegacyOp::LegacyOp(1, opNum) {
//
}
LegacyOp* LegacyStatsOp::clone() {
return new LegacyStatsOp(this->_opNum);
}
/**
* For all reductions rules are simple: either you return scalar, or you return reduced NDArray.
* It solely depends on input shape, and requested dimensions
*/
ShapeList *LegacyStatsOp::calculateOutputShape(ShapeList *inputShape, nd4j::graph::Context &block) {
auto inShape = inputShape->at(0);
Nd4jLong *newShape;
if (block.getIArguments()->size() == 0 || (block.getIArguments()->size() == 1 && INT_ARG(0) == nd4j::DataTypeUtils::max<int>())) {
// in this case we just return scalar
ALLOCATE(newShape, block.getWorkspace(), shape::shapeInfoLength(2), Nd4jLong);
newShape[0] = 2;
newShape[1] = 1;
newShape[2] = 1;
newShape[3] = 1;
newShape[4] = 1;
newShape[5] = 0;
newShape[6] = 1;
newShape[7] = 99;
} else {
// in this case we're building proper shape for reduction
auto array = new NDArray(nullptr, inShape, block.launchContext());
newShape = ShapeUtils::evalReduceShapeInfo('c', *block.getIArguments(), *array, false, true);
delete array;
}
return SHAPELIST(newShape);
}
}
}