91 lines
3.1 KiB
C++
91 lines
3.1 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
|
|
******************************************************************************/
|
|
|
|
//
|
|
// Created by raver119 on 01.11.2017.
|
|
// Modified by GS <sgazeos@gmail.com> 4/5/2018.
|
|
|
|
#include <op_boilerplate.h>
|
|
#if NOT_EXCLUDED(OP_argmin)
|
|
|
|
#include <ops/declarable/CustomOperations.h>
|
|
#include <ops/declarable/helpers/axis.h>
|
|
|
|
namespace nd4j {
|
|
namespace ops {
|
|
|
|
DECLARE_TYPES(argmin) {
|
|
getOpDescriptor()
|
|
->setAllowedInputTypes(nd4j::DataType::ANY)
|
|
->setAllowedOutputTypes({ALL_INTS});
|
|
}
|
|
|
|
CUSTOM_OP_IMPL(argmin, 1, 1, false, 0, -2) {
|
|
auto input = INPUT_VARIABLE(0);
|
|
auto axis = *block.getIArguments();
|
|
|
|
auto output = OUTPUT_VARIABLE(0);
|
|
|
|
// axis might be dynamic (i.e. tf mode)
|
|
if (block.width() > 1 && axis.size() == 0) {
|
|
auto axisVector = INPUT_VARIABLE(1);
|
|
helpers::adjustAxis(input->rankOf(), axisVector, axis);
|
|
|
|
input->applyIndexReduce(indexreduce::IndexMin, *output, axis);
|
|
} else {
|
|
helpers::adjustAxis(input->rankOf(), axis);
|
|
|
|
input->applyIndexReduce(indexreduce::IndexMin, *output, axis);
|
|
}
|
|
|
|
STORE_RESULT(output);
|
|
|
|
return ND4J_STATUS_OK;
|
|
}
|
|
|
|
DECLARE_SHAPE_FN(argmin) {
|
|
std::vector<int> dims;
|
|
auto in = inputShape->at(0);
|
|
if (block.width() == 1) {
|
|
dims = *block.getIArguments();
|
|
} else {
|
|
auto y = INPUT_VARIABLE(1);
|
|
dims = y->template asVectorT<int>();
|
|
}
|
|
|
|
// we're resolving negative axis here
|
|
helpers::adjustAxis(shape::rank(in), dims);
|
|
|
|
if (dims.size() > 1)
|
|
std::sort(dims.begin(), dims.end());
|
|
|
|
for (auto d:dims) {
|
|
REQUIRE_TRUE(inputShape->at(0)[d+1] != 0, 0, "ArgMin: you can't reduce along axis with 0 in shape");
|
|
}
|
|
|
|
// special case - output is scalar
|
|
if (dims.size() == 0 || (dims.size() == 1 && dims.at(0) == nd4j::DataTypeUtils::max<int>())) {
|
|
return SHAPELIST(ConstantShapeHelper::getInstance()->scalarShapeInfo(DataType::INT64));
|
|
}
|
|
|
|
auto newShape = ShapeUtils::evalReduceShapeInfo('c', dims, in, DataType::INT64, false, false, block.getWorkspace());
|
|
return SHAPELIST(newShape);
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
#endif |