91 lines
3.1 KiB
C++
91 lines
3.1 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// Created by raver119 on 01.11.2017.
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// Modified by GS <sgazeos@gmail.com> 4/5/2018.
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_argmin)
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/axis.h>
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namespace nd4j {
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namespace ops {
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DECLARE_TYPES(argmin) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setAllowedOutputTypes({ALL_INTS});
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}
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CUSTOM_OP_IMPL(argmin, 1, 1, false, 0, -2) {
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auto input = INPUT_VARIABLE(0);
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auto axis = *block.getIArguments();
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auto output = OUTPUT_VARIABLE(0);
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// axis might be dynamic (i.e. tf mode)
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if (block.width() > 1 && axis.size() == 0) {
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auto axisVector = INPUT_VARIABLE(1);
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helpers::adjustAxis(input->rankOf(), axisVector, axis);
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input->applyIndexReduce(indexreduce::IndexMin, output, axis);
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} else {
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helpers::adjustAxis(input->rankOf(), axis);
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input->applyIndexReduce(indexreduce::IndexMin, output, axis);
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}
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STORE_RESULT(output);
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return ND4J_STATUS_OK;
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}
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DECLARE_SHAPE_FN(argmin) {
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std::vector<int> dims;
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auto in = inputShape->at(0);
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if (block.width() == 1) {
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dims = *block.getIArguments();
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} else {
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auto y = INPUT_VARIABLE(1);
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dims = y->template asVectorT<int>();
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}
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// we're resolving negative axis here
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helpers::adjustAxis(shape::rank(in), dims);
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if (dims.size() > 1)
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std::sort(dims.begin(), dims.end());
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for (auto d:dims) {
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REQUIRE_TRUE(inputShape->at(0)[d+1] != 0, 0, "ArgMin: you can't reduce along axis with 0 in shape");
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}
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// special case - output is scalar
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if (dims.size() == 0 || (dims.size() == 1 && dims.at(0) == nd4j::DataTypeUtils::max<int>())) {
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return SHAPELIST(ConstantShapeHelper::getInstance()->scalarShapeInfo(DataType::INT64));
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}
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auto newShape = ShapeUtils::evalReduceShapeInfo('c', dims, in, DataType::INT64, false, false, block.getWorkspace());
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return SHAPELIST(newShape);
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}
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}
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}
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#endif |