71 lines
3.1 KiB
C++
71 lines
3.1 KiB
C++
/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 sgazeos@gmail.com
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//
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#include <ops/declarable/helpers/random_crop.h>
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//#include <NativeOps.h>
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#include <vector>
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#include <memory>
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#include <graph/Context.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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template <typename T>
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static int _randomCropFunctor(graph::Context& context, NDArray* input, NDArray* shape, NDArray* output, int seed) {
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graph::RandomGenerator rngX(context.getRng());
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//functions::random::RandomFunction<T>::template execTransform<randomOps::UniformDistribution<T>>(rng, output->buffer(), output->shapeInfo(), std::vector<T>({T(0.), shape->e(last)}).data());
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//NativeOpExecutioner::execRandom(random::UniformDistribution, rng, output->buffer(), output->shapeInfo(), std::vector<T>({T(0.), shape->e<T>(last)}).data());
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Nd4jLong last = shape->lengthOf() - 1;
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rngX.setSeed(seed);
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//functions::random::RandomFunction<T>::template execTransform<randomOps::UniformDistribution<T>>(rng, output->buffer(), output->shapeInfo(), std::vector<T>({T(0.), shape->getScalar(last)}).data());
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for (Nd4jLong e = 0; e < output->lengthOf(); ++e) {
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output->p(e, rngX.relativeT<T>(e, 0, shape->e<Nd4jLong>(last)));
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}
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Nd4jLong maxIndex = output->argMax();
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Nd4jLong startPos = output->e<Nd4jLong>(maxIndex);
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Nd4jLong lastDim = input->sizeAt(-1);
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// nd4j_printf("Before processing: %i %i. Output length %i\n", maxIndex, startPos, output->lengthOf());
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Nd4jLong pos = 0;
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Nd4jLong width = startPos + shape->e<Nd4jLong>(last);
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if (width >= lastDim) {
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startPos -= (width - lastDim);
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width = lastDim;
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}
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for (Nd4jLong i = 0; i < input->lengthOf(); i += lastDim) {
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for (Nd4jLong k = startPos; k < width && pos < output->lengthOf(); k++) {
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output->p(pos++, input->e<T>(i + k));
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}
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}
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return ND4J_STATUS_OK;
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}
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int randomCropFunctor(graph::Context& context, NDArray* input, NDArray* shape, NDArray* output, int seed) {
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BUILD_SINGLE_SELECTOR(input->dataType(), return _randomCropFunctor, (context, input, shape, output, seed), FLOAT_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template int _randomCropFunctor, (graph::Context& context, NDArray* input, NDArray* shape, NDArray* output, int seed), FLOAT_TYPES);
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}
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}
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} |