92 lines
3.7 KiB
C++
92 lines
3.7 KiB
C++
/*******************************************************************************
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* Copyright (c) 2019-2020 Konduit K.K.
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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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// @author Oleh Semeniv (oleg.semeniv@gmail.com)
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//
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#include <ops/declarable/helpers/updatersHelpers.h>
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#include <execution/Threads.h>
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#include <math/platformmath.h>
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#include <math/templatemath.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename T>
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static void adaGradUpdater_(const NDArray& gradient, const NDArray& initState, NDArray& update, NDArray& stateH, const double dLr, const double dEpsilon) {
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const T* grad = gradient.bufferAsT<T>();
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const T* init = initState.bufferAsT<T>();
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T* up = update.bufferAsT<T>();
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T* st = stateH.bufferAsT<T>();
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const T lr = static_cast<T>(dLr);
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const T epsilon = static_cast<T>(dEpsilon);
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bool bEws1 = 1 == gradient.ews() && 1 == update.ews() && 1 == stateH.ews() && 1 == initState.ews();
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bool bSameOrdering = gradient.ordering() == update.ordering() && update.ordering() == stateH.ordering() && stateH.ordering() == initState.ordering();
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if (bEws1 && bSameOrdering) {
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auto func = PRAGMA_THREADS_FOR{
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for (auto i = start; i < stop; i++) {
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st[i] = init[i] + grad[i] * grad[i];
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up[i] = (lr * grad[i]) / (math::nd4j_sqrt<T, T>(st[i]) + epsilon);
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}
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};
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samediff::Threads::parallel_for(func, 0, gradient.lengthOf(), 1);
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return;
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}
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bool bXZsame = shape::haveSameShapeAndStrides(gradient.getShapeInfo(), update.getShapeInfo());
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bool bXInSame = shape::haveSameShapeAndStrides(gradient.getShapeInfo(), initState.getShapeInfo());
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bool bXStSame = shape::haveSameShapeAndStrides(gradient.getShapeInfo(), stateH.getShapeInfo());
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auto func = PRAGMA_THREADS_FOR{
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int coords[MAX_RANK];
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for (auto i = start; i < stop; i++) {
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shape::index2coordsCPU(start, i, gradient.getShapeInfo(), coords);
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const auto xOffset = shape::getOffset(gradient.getShapeInfo(), coords);
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const auto zOffset = bXZsame ? xOffset : shape::getOffset(update.getShapeInfo(), coords);
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const auto initOffset = bXInSame ? xOffset : shape::getOffset(initState.getShapeInfo(), coords);
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const auto stOffset = bXStSame ? xOffset : shape::getOffset(stateH.getShapeInfo(), coords);
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st[stOffset] = init[initOffset] + grad[xOffset] * grad[xOffset];
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up[zOffset] = (lr * grad[xOffset]) / (math::nd4j_sqrt<T, T>(st[stOffset]) + epsilon);
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}
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};
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samediff::Threads::parallel_for(func, 0, gradient.lengthOf(), 1);
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return;
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}
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void updaterAdaGrad(sd::LaunchContext* context, const NDArray& gradient, const NDArray& initState, NDArray& update, NDArray& stateH,
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const double dLr, const double dEpsilon) {
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BUILD_SINGLE_SELECTOR(gradient.dataType(), adaGradUpdater_, (gradient, initState, update, stateH, dLr, dEpsilon), FLOAT_TYPES);
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}
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}
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}
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}
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