/*******************************************************************************
* 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 <iomanip>
#include <iostream>
#include <CL/sycl.hpp>
#ifndef ONEDAL_DATA_PARALLEL
#define ONEDAL_DATA_PARALLEL
#endif
#include "oneapi/dal/algo/pca.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("pca_normalized.csv");
const auto x_train = dal::read<dal::table>(q, dal::csv::data_source{ train_data_file_name });
const auto pca_desc = dal::pca::descriptor<>().set_component_count(5).set_deterministic(true);
const auto result_train = dal::train(q, pca_desc, x_train);
std::cout << "Eigenvectors:\n" << result_train.get_eigenvectors() << std::endl;
std::cout << "Eigenvalues:\n" << result_train.get_eigenvalues() << std::endl;
const auto result_infer = dal::infer(q, pca_desc, result_train.get_model(), x_train);
std::cout << "Transformed data:\n" << result_infer.get_transformed_data() << 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>() << "\n" << std::endl;
auto q = sycl::queue{ d };
run(q);
}
return 0;
}
