cavis/libnd4j/include/ops/declarable/generic/reduce/argmin.cpp

100 lines
3.4 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 <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_argmin)
#include <ops/declarable/helpers/axis.h>
#include <ops/declarable/helpers/reductions.h>
#include <ops/declarable/CustomOperations.h>
#include <helpers/ConstantTadHelper.h>
namespace sd {
namespace ops {
DECLARE_TYPES(argmin) {
getOpDescriptor()
->setAllowedInputTypes({ ALL_FLOATS,ALL_INTS })
->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);
if (output->isEmpty())
return Status::OK();
// 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);
helpers::argMin(*input, *output, axis);
}
else {
helpers::argMin(*input, *output, axis);
}
STORE_RESULT(output);
return ND4J_STATUS_OK;
}
DECLARE_SHAPE_FN(argmin) {
std::vector<int> dims;
if (block.width() == 1) {
dims = *block.getIArguments();
} else {
auto y = INPUT_VARIABLE(1);
dims = y->template asVectorT<int>();
}
auto keepDims = block.numB() ? B_ARG(0) : false;
auto dtype = block.numD() ? D_ARG(0) : DataType::INT64;
// we're resolving negative axis here
helpers::adjustAxis(shape::rank(inputShape->at(0)), dims);
auto in = inputShape->at(0);
for (auto d : dims) {
// we have special case here
if (d == sd::DataTypeUtils::max<int>())
continue;
REQUIRE_TRUE(d < shape::rank(in), 0, "ArgMin: axis can't be above rank")
REQUIRE_TRUE(in[d + 1] != 0, 0, "ArgMin: you can't reduce along axis with 0 in shape");
}
// special case - output is scalar
if (dims.empty() || (dims.size() == 1 && dims.at(0) == sd::DataTypeUtils::max<int>())) {
return SHAPELIST(ConstantShapeHelper::getInstance().scalarShapeInfo(dtype));
}
return SHAPELIST(ShapeUtils::evalReduceShapeInfo('c', dims, inputShape->at(0), dtype, keepDims, false, block.getWorkspace()));
}
}
}
#endif