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

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/*******************************************************************************
* 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 raver119@gmail.com
//
#include <ops/declarable/helpers/flatten.h>
namespace nd4j {
namespace ops {
namespace helpers {
template <typename T>
static void flatten_(std::vector<NDArray*> &inputs, NDArray *output, const char order) {
int numArrays = inputs.size();
std::vector<Nd4jLong> offsets(numArrays);
Nd4jLong cOffset = 0;
// calculating offsets in output
for (int e = 0; e < numArrays; e++) {
offsets[e] = cOffset;
cOffset += inputs[e]->lengthOf();
}
// actually transferring data
for (int e = 0; e < numArrays; e++) {
auto z = reinterpret_cast<T *>(output->bufferWithOffset(offsets[e]));
auto xBuffer = inputs[e]->bufferAsT<T>();
auto xShapeInfo = inputs[e]->shapeInfo();
auto xLength = inputs[e]->lengthOf();
for (Nd4jLong i = 0; i < xLength; i++)
z[i] = xBuffer[getIndexOffsetOrdered(i, xShapeInfo, order)];
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}
}
void flatten(nd4j::LaunchContext *context, std::vector<NDArray*> &inputs, NDArray *output, char order) {
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BUILD_SINGLE_SELECTOR(output->dataType(), flatten_, (inputs, output, order), LIBND4J_TYPES);
}
}
}
}