qn_mg.hpp

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/*
 * Copyright (c) 2023-2024, NVIDIA 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 <cuml/common/logger.hpp>
#include <cuml/linear_model/qn.h>
 
#include <cumlprims/opg/matrix/data.hpp>
#include <cumlprims/opg/matrix/part_descriptor.hpp>
#include <raft/core/comms.hpp>
 
#include <cuda_runtime.h>
 
#include <vector>
using namespace MLCommon;
 
namespace ML {
namespace GLM {
namespace opg {
 
std::vector<float> getUniquelabelsMG(const raft::handle_t& handle,
                                     Matrix::PartDescriptor& input_desc,
                                     std::vector<Matrix::Data<float>*>& labels);
 
void qnFit(raft::handle_t& handle,
           std::vector<Matrix::Data<float>*>& input_data,
           Matrix::PartDescriptor& input_desc,
           std::vector<Matrix::Data<float>*>& labels,
           float* coef,
           const qn_params& pams,
           bool X_col_major,
           bool standardization,
           int n_classes,
           float* f,
           int* num_iters);
 
void qnFitSparse(raft::handle_t& handle,
                 std::vector<Matrix::Data<float>*>& input_values,
                 int* input_cols,
                 int* input_row_ids,
                 int X_nnz,
                 Matrix::PartDescriptor& input_desc,
                 std::vector<Matrix::Data<float>*>& labels,
                 float* coef,
                 const qn_params& pams,
                 bool standardization,
                 int n_classes,
                 float* f,
                 int* num_iters);
 
};  // namespace opg
};  // namespace GLM
};  // namespace ML