#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>
Go to the source code of this file.
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template<typename T > |
std::vector< T > | ML::GLM::opg::getUniquelabelsMG (const raft::handle_t &handle, Matrix::PartDescriptor &input_desc, std::vector< Matrix::Data< T > * > &labels) |
| Calculate unique class labels across multiple GPUs in a multi-node environment. More...
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template<typename T > |
void | ML::GLM::opg::qnFit (raft::handle_t &handle, std::vector< Matrix::Data< T > * > &input_data, Matrix::PartDescriptor &input_desc, std::vector< Matrix::Data< T > * > &labels, T *coef, const qn_params &pams, bool X_col_major, bool standardization, int n_classes, T *f, int *num_iters) |
| performs MNMG fit operation for the logistic regression using quasi newton methods More...
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template<typename T , typename I > |
void | ML::GLM::opg::qnFitSparse (raft::handle_t &handle, std::vector< Matrix::Data< T > * > &input_values, I *input_cols, I *input_row_ids, I X_nnz, Matrix::PartDescriptor &input_desc, std::vector< Matrix::Data< T > * > &labels, T *coef, const qn_params &pams, bool standardization, int n_classes, T *f, int *num_iters) |
| support sparse vectors (Compressed Sparse Row format) for MNMG logistic regression fit using quasi newton methods More...
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