/******************************************************************************* * 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 // #include #include namespace nd4j { namespace ops { namespace helpers { template void _confusionFunctor(NDArray* labels, NDArray* predictions, NDArray* weights, NDArray* output) { ResultSet arrs = output->allTensorsAlongDimension({1}); int lLen = labels->lengthOf(); auto func = PRAGMA_THREADS_FOR { for (int j = start; j < stop; j++) { auto label = labels->e(j); auto pred = predictions->e(j); T value = (weights == nullptr ? (T) 1.0f : weights->e(j)); arrs.at(label)->p(pred, value); } }; samediff::Threads::parallel_for(func, 0, lLen); } void confusionFunctor(nd4j::LaunchContext * context, NDArray* labels, NDArray* predictions, NDArray* weights, NDArray* output) { auto xType = output->dataType(); // weights can be null BUILD_SINGLE_SELECTOR(xType, _confusionFunctor, (labels, predictions, weights, output), NUMERIC_TYPES); } BUILD_SINGLE_TEMPLATE(template void _confusionFunctor, (NDArray* labels, NDArray* predictions, NDArray* weights, NDArray* output);, NUMERIC_TYPES); } } }