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Merge branch 'branch-24.06' into fix/cccl-2.5
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@dantegd
dantegd authored May 22, 2024
2 parents d9e3f5a + f16fccc commit da73a08
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Showing 4 changed files with 296 additions and 131 deletions.
25 changes: 14 additions & 11 deletions cpp/include/cuml/linear_model/qn_mg.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -37,9 +37,10 @@ namespace opg {
* @param[in] labels: labels data
* @returns host vector that stores the distinct labels
*/
std::vector<float> getUniquelabelsMG(const raft::handle_t& handle,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels);
template <typename T>
std::vector<T> getUniquelabelsMG(const raft::handle_t& handle,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<T>*>& labels);

/**
* @brief performs MNMG fit operation for the logistic regression using quasi newton methods
Expand All @@ -55,16 +56,17 @@ std::vector<float> getUniquelabelsMG(const raft::handle_t& handle,
* @param[out] f: host pointer holding the final objective value
* @param[out] num_iters: host pointer holding the actual number of iterations taken
*/
template <typename T>
void qnFit(raft::handle_t& handle,
std::vector<Matrix::Data<float>*>& input_data,
std::vector<Matrix::Data<T>*>& input_data,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels,
float* coef,
std::vector<Matrix::Data<T>*>& labels,
T* coef,
const qn_params& pams,
bool X_col_major,
bool standardization,
int n_classes,
float* f,
T* f,
int* num_iters);

/**
Expand All @@ -86,18 +88,19 @@ void qnFit(raft::handle_t& handle,
* @param[out] f: host pointer holding the final objective value
* @param[out] num_iters: host pointer holding the actual number of iterations taken
*/
template <typename T>
void qnFitSparse(raft::handle_t& handle,
std::vector<Matrix::Data<float>*>& input_values,
std::vector<Matrix::Data<T>*>& input_values,
int* input_cols,
int* input_row_ids,
int X_nnz,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels,
float* coef,
std::vector<Matrix::Data<T>*>& labels,
T* coef,
const qn_params& pams,
bool standardization,
int n_classes,
float* f,
T* f,
int* num_iters);

}; // namespace opg
Expand Down
147 changes: 105 additions & 42 deletions cpp/src/glm/qn_mg.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -183,42 +183,76 @@ void qnFit_impl(raft::handle_t& handle,
input_desc.uniqueRanks().size());
}

std::vector<float> getUniquelabelsMG(const raft::handle_t& handle,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels)
template <typename T>
std::vector<T> getUniquelabelsMG(const raft::handle_t& handle,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<T>*>& labels)
{
RAFT_EXPECTS(labels.size() == 1,
"getUniqueLabelsMG currently does not accept more than one data chunk");
Matrix::Data<float>* data_y = labels[0];
int n_rows = input_desc.totalElementsOwnedBy(input_desc.rank);
return distinct_mg<float>(handle, data_y->ptr, n_rows);
Matrix::Data<T>* data_y = labels[0];
size_t n_rows = input_desc.totalElementsOwnedBy(input_desc.rank);
return distinct_mg<T>(handle, data_y->ptr, n_rows);
}

template std::vector<float> getUniquelabelsMG(const raft::handle_t& handle,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels);

template std::vector<double> getUniquelabelsMG(const raft::handle_t& handle,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<double>*>& labels);

template <typename T>
void qnFit(raft::handle_t& handle,
std::vector<Matrix::Data<float>*>& input_data,
std::vector<Matrix::Data<T>*>& input_data,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels,
float* coef,
std::vector<Matrix::Data<T>*>& labels,
T* coef,
const qn_params& pams,
bool X_col_major,
bool standardization,
int n_classes,
float* f,
T* f,
int* num_iters)
{
qnFit_impl<float>(handle,
input_data,
input_desc,
labels,
coef,
pams,
X_col_major,
standardization,
n_classes,
f,
num_iters);
qnFit_impl<T>(handle,
input_data,
input_desc,
labels,
coef,
pams,
X_col_major,
standardization,
n_classes,
f,
num_iters);
}

template 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);

template void qnFit(raft::handle_t& handle,
std::vector<Matrix::Data<double>*>& input_data,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<double>*>& labels,
double* coef,
const qn_params& pams,
bool X_col_major,
bool standardization,
int n_classes,
double* f,
int* num_iters);

template <typename T, typename I>
void qnFitSparse_impl(const raft::handle_t& handle,
const qn_params& pams,
Expand Down Expand Up @@ -269,18 +303,19 @@ void qnFitSparse_impl(const raft::handle_t& handle,
return;
}

template <typename T>
void qnFitSparse(raft::handle_t& handle,
std::vector<Matrix::Data<float>*>& input_values,
std::vector<Matrix::Data<T>*>& input_values,
int* input_cols,
int* input_row_ids,
int X_nnz,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<float>*>& labels,
float* coef,
std::vector<Matrix::Data<T>*>& labels,
T* coef,
const qn_params& pams,
bool standardization,
int n_classes,
float* f,
T* f,
int* num_iters)
{
RAFT_EXPECTS(input_values.size() == 1,
Expand All @@ -289,25 +324,53 @@ void qnFitSparse(raft::handle_t& handle,
auto data_input_values = input_values[0];
auto data_y = labels[0];

qnFitSparse_impl<float, int>(handle,
pams,
data_input_values->ptr,
input_cols,
input_row_ids,
X_nnz,
standardization,
data_y->ptr,
input_desc.totalElementsOwnedBy(input_desc.rank),
input_desc.N,
n_classes,
coef,
f,
num_iters,
input_desc.M,
input_desc.rank,
input_desc.uniqueRanks().size());
qnFitSparse_impl<T, int>(handle,
pams,
data_input_values->ptr,
input_cols,
input_row_ids,
X_nnz,
standardization,
data_y->ptr,
input_desc.totalElementsOwnedBy(input_desc.rank),
input_desc.N,
n_classes,
coef,
f,
num_iters,
input_desc.M,
input_desc.rank,
input_desc.uniqueRanks().size());
}

template 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);

template void qnFitSparse(raft::handle_t& handle,
std::vector<Matrix::Data<double>*>& input_values,
int* input_cols,
int* input_row_ids,
int X_nnz,
Matrix::PartDescriptor& input_desc,
std::vector<Matrix::Data<double>*>& labels,
double* coef,
const qn_params& pams,
bool standardization,
int n_classes,
double* f,
int* num_iters);

}; // namespace opg
}; // namespace GLM
}; // namespace ML
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