89 lines
3.5 KiB
C++
89 lines
3.5 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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// Created by george@skymind.io on 2/21/2018.
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// Modified by sgazeos@gmail.com on 4/4/2018
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_sufficient_statistics)
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/axis.h>
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namespace nd4j {
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namespace ops {
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CUSTOM_OP_IMPL(sufficient_statistics, 2, 3, false, 0, 0) {
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auto input = INPUT_VARIABLE(0);
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auto axisVector = INPUT_VARIABLE(1);
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auto dataCount = OUTPUT_VARIABLE(0);
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auto sum = OUTPUT_VARIABLE(1);
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auto squares = OUTPUT_VARIABLE(2);
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std::vector<int> axis(axisVector->lengthOf());//*block.getIArguments();
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// axis might be dynamic (i.e. tf mode)
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helpers::adjustAxis(input->rankOf(), axisVector, axis);
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input->reduceAlongDimension(reduce::SquaredNorm, squares, axis);
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input->reduceAlongDimension(reduce::Sum, sum, axis);
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auto count = NDArrayFactory::create(input->dataType(), input->lengthOf() / sum->lengthOf());
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dataCount->assign(count);
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if (block.numT() > 0) {
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auto shift = OUTPUT_VARIABLE(3);
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shift->assign(T_ARG(0));
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}
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return Status::OK();
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}
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DECLARE_TYPES(sufficient_statistics) {
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getOpDescriptor()
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->setAllowedInputTypes(0, {ALL_INTS, ALL_FLOATS});
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getOpDescriptor()
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->setAllowedInputTypes(1, {DataType::INT32, DataType::INT64});
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getOpDescriptor()
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->setAllowedOutputTypes(0, DataType::INHERIT);
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getOpDescriptor()
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->setAllowedOutputTypes(1, DataType::INHERIT);
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getOpDescriptor()
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->setAllowedOutputTypes(2, DataType::INHERIT);
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}
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DECLARE_SHAPE_FN(sufficient_statistics) {
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auto axisVector = INPUT_VARIABLE(1);
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std::vector<int> axis(axisVector->lengthOf());
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auto input = INPUT_VARIABLE(0);
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helpers::adjustAxis(input->rankOf(), axisVector, axis);
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//std::vector<int> dims = ShapeUtils::evalDimsToExclude(input->rankOf(), {axis});
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auto scalarShape = ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(inputShape->at(0)));
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auto sumShape = ShapeUtils::evalReduceShapeInfo('c', axis, *input, false, false, block.workspace());
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auto squareShape = ShapeUtils::evalReduceShapeInfo('c', axis, *input, false, false, block.workspace());
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auto shapeList = SHAPELIST(scalarShape, sumShape, squareShape);
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if (block.numT() > 0)
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shapeList->push_back(ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(inputShape->at(0))));
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return shapeList;
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}
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}
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}
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#endif |