cavis/libnd4j/include/ops/declarable/helpers/cpu/random_crop.cpp

71 lines
3.1 KiB
C++

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