Developer Guide and Reference

  • 2021.2
  • 03/26/2021
  • Public Content
Contents

kmeans_lloyd_dense_batch.cpp

/******************************************************************************* * Copyright 2020-2021 Intel Corporation * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://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. *******************************************************************************/ #include <CL/sycl.hpp> #include <iomanip> #include <iostream> #define ONEDAL_DATA_PARALLEL #include "oneapi/dal/algo/kmeans.hpp" #include "oneapi/dal/io/csv.hpp" #include "example_util/utils.hpp" namespace dal = oneapi::dal; void run(sycl::queue &q) { const auto train_data_file_name = get_data_path("kmeans_dense_train_data.csv"); const auto initial_centroids_file_name = get_data_path("kmeans_dense_train_centroids.csv"); const auto test_data_file_name = get_data_path("kmeans_dense_test_data.csv"); const auto test_label_file_name = get_data_path("kmeans_dense_test_label.csv"); const auto x_train = dal::read<dal::table>(q, dal::csv::data_source{ train_data_file_name }); const auto initial_centroids = dal::read<dal::table>(q, dal::csv::data_source{ initial_centroids_file_name }); const auto x_test = dal::read<dal::table>(q, dal::csv::data_source{ test_data_file_name }); const auto y_test = dal::read<dal::table>(q, dal::csv::data_source{ test_label_file_name }); const auto kmeans_desc = dal::kmeans::descriptor<>() .set_cluster_count(20) .set_max_iteration_count(5) .set_accuracy_threshold(0.001); const auto result_train = dal::train(q, kmeans_desc, x_train, initial_centroids); std::cout << "Iteration count: " << result_train.get_iteration_count() << std::endl; std::cout << "Objective function value: " << result_train.get_objective_function_value() << std::endl; std::cout << "Labels:\n" << result_train.get_labels() << std::endl; std::cout << "Centroids:\n" << result_train.get_model().get_centroids() << std::endl; const auto result_test = dal::infer(q, kmeans_desc, result_train.get_model(), x_test); std::cout << "Infer result:\n" << result_test.get_labels() << std::endl; std::cout << "Ground truth:\n" << y_test << std::endl; } int main(int argc, char const *argv[]) { for (auto d : list_devices()) { std::cout << "Running on " << d.get_info<sycl::info::device::name>() << std::endl; auto q = sycl::queue{ d }; run(q); } return 0; }

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