* omp threads backported Signed-off-by: raver119 <raver119@gmail.com> * omp scalar reduce Signed-off-by: raver119 <raver119@gmail.com> * timing Signed-off-by: raver119 <raver119@gmail.com> * timing Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * namespace change Signed-off-by: raver119 <raver119@gmail.com> * num_threads Signed-off-by: raver119 <raver119@gmail.com> * one minor fix Signed-off-by: raver119 <raver119@gmail.com>
		
			
				
	
	
		
			212 lines
		
	
	
		
			7.8 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			212 lines
		
	
	
		
			7.8 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 Yurii Shyrma, created on 21.09.2018
 | |
| // @author raver119@gmail.com
 | |
| //
 | |
| 
 | |
| 
 | |
| #include <helpers/TAD.h>
 | |
| #include<ops/declarable/helpers/ismax.h>
 | |
| #include <helpers/ConstantTadHelper.h>
 | |
| #include <execution/Threads.h>
 | |
| 
 | |
| namespace sd 	  {
 | |
| namespace ops 	  {
 | |
| namespace helpers {
 | |
| 
 | |
| template <typename X, typename Z>
 | |
| static void ismax_(const NDArray* input, NDArray* output, const std::vector<int>& dimensions) {
 | |
| 
 | |
|     if (input->isVector()) {
 | |
|         int dimensionsLength = dimensions.size();
 | |
|         int length = input->lengthOf();
 | |
|         if (!dimensions.empty() && (input->shapeOf())[dimensions[0]] == 1) {
 | |
|             for (int i = 0; i < length; i++)
 | |
|                 output->p<Z>(i, 1);
 | |
|         }
 | |
|         else {
 | |
|             int eleStride = shape::elementWiseStride(input->getShapeInfo());
 | |
|             if (eleStride == 1) {
 | |
|                 int maxIdx = 0;
 | |
|                 auto currMax = input->e<X>(0);
 | |
|                 if (length < ELEMENT_THRESHOLD) {
 | |
| 
 | |
|                     for (int i = 0; i < length; i++) {
 | |
|                         if (currMax < input->e<X>(i)) {
 | |
|                             currMax = input->e<X>(i);
 | |
|                             maxIdx = i;
 | |
|                         }
 | |
|                         output->p<Z>(i, 0);
 | |
|                     }
 | |
|                 }
 | |
|                 else {
 | |
| 
 | |
|                     {
 | |
|                         int maxIdxLocal = maxIdx;
 | |
|                         auto currMaxLocal = currMax;
 | |
| 
 | |
|                         for (int i = 0; i < length; i++) {
 | |
|                             if (currMaxLocal < input->e<X>(i)) {
 | |
|                                 currMaxLocal = input->e<X>(i);
 | |
|                                 maxIdxLocal = i;
 | |
|                             }
 | |
|                             output->p<Z>(i, 0);
 | |
|                         }
 | |
| 
 | |
|                         PRAGMA_OMP_CRITICAL
 | |
|                         {
 | |
|                             if (currMax < currMaxLocal) {
 | |
|                                 currMax = currMaxLocal;
 | |
|                                 maxIdx = maxIdxLocal;
 | |
|                             }
 | |
|                         }
 | |
|                     }
 | |
|                 }
 | |
|                 output->p<Z>(maxIdx, 1);
 | |
|             }
 | |
|             else {
 | |
|                 int maxIdx = 0;
 | |
|                 auto currMax = input->e<X>(0);
 | |
|                 if (length < ELEMENT_THRESHOLD) {
 | |
| 
 | |
|                     for (int i = 0; i < length; i++) {
 | |
|                         if (currMax < input->e<X>(i)) {
 | |
|                             currMax = input->e<X>(i);
 | |
|                             maxIdx = i;
 | |
|                         }
 | |
|                         output->p<Z>(i, 0.f);
 | |
|                     }
 | |
|                 }
 | |
|                 else {
 | |
| 
 | |
|                     {
 | |
|                         int maxIdxLocal = maxIdx;
 | |
|                         auto currMaxLocal = currMax;
 | |
|                         for (int i = 0; i < length; i++) {
 | |
|                             if (currMaxLocal < input->e<X>(i)) {
 | |
|                                 currMaxLocal = input->e<X>(i);
 | |
|                                        maxIdxLocal = i;
 | |
|                             }
 | |
|                             output->p<Z>(i, 0.f);
 | |
|                         }
 | |
| 
 | |
|                         PRAGMA_OMP_CRITICAL
 | |
|                         {
 | |
|                             if (currMax < currMaxLocal) {
 | |
|                                 currMax = currMaxLocal;
 | |
|                                 maxIdx = maxIdxLocal;
 | |
|                             }
 | |
|                         }
 | |
|                     }
 | |
|                 }
 | |
|                 output->p<Z>(maxIdx, 1);
 | |
|             }
 | |
|         }
 | |
|     }
 | |
|     else {
 | |
|         int dimensionsLength = dimensions.size();
 | |
|         //int tads = tad.numTads;
 | |
|         //decompose in to several sub tads after
 | |
|         //moving all dimensions (in sorted order)
 | |
|         //to the back.
 | |
|         //permuted version of the input shape info for setting up the tad problem
 | |
|         auto tadPack = sd::ConstantTadHelper::getInstance()->tadForDimensions(input->getShapeInfo(), const_cast<int*>(dimensions.data()), dimensionsLength);
 | |
|         auto tadPackZ = sd::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), const_cast<int*>(dimensions.data()), dimensionsLength);
 | |
| 
 | |
| 
 | |
|         auto tadShapeShapeInfo = tadPack.primaryShapeInfo();
 | |
|         auto tadOffsets = tadPack.primaryOffsets();
 | |
|         auto zOfsets = tadPackZ.platformOffsets();
 | |
| 
 | |
|         int tadLength = shape::length(tadShapeShapeInfo);
 | |
|         int tads = tadPack.numberOfTads();
 | |
| 
 | |
|         int tadsPerThread = tads / TAD_THRESHOLD;
 | |
|         int num_threads = sd::math::nd4j_max<int>(1, tadsPerThread);
 | |
|         num_threads = sd::math::nd4j_min<int>(num_threads, omp_get_max_threads());
 | |
| 
 | |
|         auto tadEWS = shape::elementWiseStride(tadShapeShapeInfo);
 | |
|         auto zEWS = shape::elementWiseStride(tadPackZ.primaryShapeInfo());
 | |
| 
 | |
|         int span = (tads / num_threads) + 8;
 | |
| 
 | |
|         auto func = PRAGMA_THREADS_FOR {
 | |
|             for (auto r = start; r < stop; r++) {
 | |
|                     auto rX = const_cast<NDArray*>(input)->bufferAsT<X>() + tadOffsets[r];
 | |
|                     auto rZ = output->bufferAsT<Z>() + zOfsets[r];
 | |
| 
 | |
|                     auto maxValue = rX[0];
 | |
|                     int maxIdx = 0;
 | |
|                     if (tadEWS == 1 && zEWS == 1) {
 | |
|                         for (int i = 0; i < tadLength; i++) {
 | |
|                             if (rX[i] > maxValue) {
 | |
|                                 maxIdx = i;
 | |
|                                 maxValue = rX[i];
 | |
|                             }
 | |
|                         }
 | |
| 
 | |
|                         PRAGMA_OMP_SIMD
 | |
|                         for (int i = 0; i < tadLength; i++) {
 | |
|                             rZ[i] = maxIdx == i ? (Z) 1 : (Z) 0;
 | |
|                         }
 | |
|                     }
 | |
|                     else if (tadEWS > 1 && zEWS > 1) {
 | |
|                         for (int i = 0; i < tadLength; i++) {
 | |
|                             if (rX[i * tadEWS] > maxValue) {
 | |
|                                 maxIdx = i;
 | |
|                                 maxValue = rX[i * tadEWS];
 | |
|                             }
 | |
|                         }
 | |
| 
 | |
|                         PRAGMA_OMP_SIMD
 | |
|                         for (int i = 0; i < tadLength; i++) {
 | |
|                             rZ[i * zEWS] = maxIdx == i ? (Z) 1 : (Z) 0;
 | |
|                         }
 | |
|                     } else {
 | |
|                         for (int i = 0; i < tadLength; i++) {
 | |
|                             auto xOffset = shape::getIndexOffset(i, tadShapeShapeInfo);
 | |
|                             if (rX[xOffset] > maxValue) {
 | |
|                                 maxIdx = i;
 | |
|                                 maxValue = rX[xOffset];
 | |
|                             }
 | |
|                         }
 | |
| 
 | |
|                         PRAGMA_OMP_SIMD
 | |
|                         for (int i = 0; i < tadLength; i++) {
 | |
|                             auto zOffset = shape::getIndexOffset(i, tadPackZ.primaryShapeInfo());
 | |
|                             rZ[zOffset] = maxIdx == i ? (Z) 1 : (Z) 0;
 | |
|                         }
 | |
|                     }
 | |
|             }
 | |
|         };
 | |
| 
 | |
|         sd::Threads::parallel_tad(func, 0, tads);
 | |
|     }
 | |
| }
 | |
| 
 | |
| 
 | |
| void ismax(sd::LaunchContext * context, const NDArray *input, NDArray *output, const std::vector<int>& dimensions) {
 | |
|     BUILD_DOUBLE_SELECTOR(input->dataType(), output->dataType(), ismax_, (input, output, dimensions), LIBND4J_TYPES, LIBND4J_TYPES);
 | |
| }
 | |
| 
 | |
| 
 | |
| }
 | |
| }
 | |
| }
 | |
| 
 |