#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>
Include dependency graph for qn_mg.hpp:
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Namespaces | |
| ML | |
| ML::GLM | |
| ML::GLM::opg | |
Functions | |
| 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... | |
| 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... | |
| 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... | |
