82 lines
2.9 KiB
C++
82 lines
2.9 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 GS <sgazeos@gmail.com>
|
|
//
|
|
|
|
#include <op_boilerplate.h>
|
|
#if NOT_EXCLUDED(OP_dynamic_stitch)
|
|
|
|
#include <ops/declarable/CustomOperations.h>
|
|
#include <ops/declarable/helpers/dynamic.h>
|
|
|
|
namespace nd4j {
|
|
namespace ops {
|
|
CUSTOM_OP_IMPL(dynamic_stitch, 2, 1, false, 0, 0) {
|
|
int numOfData = block.width();
|
|
// int k = 0;
|
|
REQUIRE_TRUE(numOfData % 2 == 0, 0,
|
|
"dynamic_stitch: The input params should contains"
|
|
" both indeces and data lists with same length.");
|
|
numOfData /= 2;
|
|
|
|
auto output = OUTPUT_VARIABLE(0);
|
|
std::vector<NDArray*> inputs(numOfData);
|
|
std::vector<NDArray*> indices(numOfData);
|
|
for (int e = 0; e < numOfData; e++) {
|
|
auto data = INPUT_VARIABLE(numOfData + e);
|
|
auto index = INPUT_VARIABLE(e);
|
|
inputs[e] = data;
|
|
indices[e] = index;
|
|
}
|
|
|
|
return helpers::dynamicStitchFunctor(block.launchContext(), inputs, indices, output);
|
|
}
|
|
|
|
DECLARE_TYPES(dynamic_stitch) {
|
|
getOpDescriptor()
|
|
->setAllowedInputTypes(nd4j::DataType::ANY)
|
|
->setAllowedOutputTypes({ALL_INTS, ALL_FLOATS});
|
|
}
|
|
|
|
DECLARE_SHAPE_FN(dynamic_stitch) {
|
|
Nd4jLong maxValue = 0;
|
|
auto numOfData = block.width();
|
|
numOfData /= 2; // only index part it's needed to review
|
|
auto restShape = inputShape->at(numOfData);
|
|
auto firstShape = inputShape->at(0);
|
|
for(int i = 0; i < numOfData; i++) {
|
|
auto input = INPUT_VARIABLE(i);
|
|
|
|
// FIXME: we have reduce::Max, cinsider using it instead
|
|
auto maxV = input->reduceNumber(reduce::Max);
|
|
if (maxV.e<Nd4jLong>(0) > maxValue) maxValue = maxV.e<Nd4jLong>(0);
|
|
}
|
|
|
|
int outRank = shape::rank(restShape) - shape::rank(firstShape) + 1;
|
|
std::vector<Nd4jLong> outShape(outRank);
|
|
|
|
outShape[0] = maxValue + 1;
|
|
for(int i = 1; i < outRank; ++i)
|
|
outShape[i] = shape::sizeAt(restShape, i);
|
|
|
|
return SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(ShapeDescriptor(ArrayOptions::dataType(restShape), shape::order(firstShape), outShape)));
|
|
}
|
|
}
|
|
}
|
|
|
|
#endif |