Developer Guide and Reference

  • 2021.4
  • 09/27/2021
  • Public Content
Contents

knn_search_brute_force_dense_batch.cpp

/******************************************************************************* * Copyright 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 "oneapi/dal/algo/knn.hpp" #include "oneapi/dal/io/csv.hpp" #include "example_util/utils.hpp" namespace dal = oneapi::dal; namespace knn = dal::knn; int main(int argc, char const *argv[]) { const auto train_data_file_name = get_data_path("k_nearest_neighbors_train_data.csv"); const auto query_data_file_name = get_data_path("k_nearest_neighbors_test_data.csv"); const auto x_train = dal::read<dal::table>(dal::csv::data_source{ train_data_file_name }); const auto x_query = dal::read<dal::table>(dal::csv::data_source{ query_data_file_name }); using cosine_desc_t = dal::cosine_distance::descriptor<float>; const auto cosine_desc = cosine_desc_t{}; const std::size_t neighbors_count = 6; const auto knn_desc = knn::descriptor<float, knn::method::brute_force, knn::task::search, cosine_desc_t>( neighbors_count, cosine_desc); const auto train_result = dal::train(knn_desc, x_train); const auto test_result = dal::infer(knn_desc, x_query, train_result.get_model()); std::cout << "Indices result:\n" << test_result.get_indices() << std::endl; std::cout << "Distance result:\n" << test_result.get_distances() << std::endl; return 0; }

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