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

/*******************************************************************************
 * Copyright (c) 2015-2018 Skymind, Inc.
 * Copyright (c) 2019 Konduit K.K.
 * 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 Abdelrauf 2020 (based on argmax)

#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_argamax)

#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(argamax) {
            getOpDescriptor()
                ->setAllowedInputTypes({ ALL_FLOATS,ALL_INTS })
                ->setAllowedOutputTypes({ ALL_INTS });
        }

        CUSTOM_OP_IMPL(argamax, 1, 1, false, 0, -2) {
            auto input = INPUT_VARIABLE(0);
            auto output = OUTPUT_VARIABLE(0);

            if (output->isEmpty())
                return Status::OK();

            auto axis = *block.getIArguments();

            // 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::argAbsMax(*input, *output, axis);
            }
            else {
                helpers::argAbsMax(*input, *output, axis);
            }

            STORE_RESULT(output);

            return Status::OK();
        }

        DECLARE_SHAPE_FN(argamax) {
            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, "ArgAmax: axis can't be above rank")
                REQUIRE_TRUE(in[d + 1] != 0, 0, "ArgAmax: 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