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Merge pull request #39 from betochimas/branch-22.06
Define C API for eigenvector centrality (rapidsai#2180)
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/* | ||
* Copyright (c) 2022, 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. | ||
*/ | ||
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#include <cugraph_c/algorithms.h> | ||
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#include <c_api/centrality_result.hpp> | ||
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extern "C" cugraph_type_erased_device_array_view_t* cugraph_centrality_result_get_vertices( | ||
cugraph_centrality_result_t* result) | ||
{ | ||
auto internal_pointer = reinterpret_cast<cugraph::c_api::cugraph_centrality_result_t*>(result); | ||
return reinterpret_cast<cugraph_type_erased_device_array_view_t*>( | ||
internal_pointer->vertex_ids_->view()); | ||
} | ||
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extern "C" cugraph_type_erased_device_array_view_t* cugraph_centrality_result_get_values( | ||
cugraph_centrality_result_t* result) | ||
{ | ||
auto internal_pointer = reinterpret_cast<cugraph::c_api::cugraph_centrality_result_t*>(result); | ||
return reinterpret_cast<cugraph_type_erased_device_array_view_t*>( | ||
internal_pointer->values_->view()); | ||
} | ||
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extern "C" void cugraph_centrality_result_free(cugraph_centrality_result_t* result) | ||
{ | ||
auto internal_pointer = reinterpret_cast<cugraph::c_api::cugraph_centrality_result_t*>(result); | ||
delete internal_pointer->vertex_ids_; | ||
delete internal_pointer->values_; | ||
delete internal_pointer; | ||
} |
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/* | ||
* Copyright (c) 2022, 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. | ||
*/ | ||
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#pragma once | ||
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#include <c_api/array.hpp> | ||
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namespace cugraph { | ||
namespace c_api { | ||
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struct cugraph_centrality_result_t { | ||
cugraph_type_erased_device_array_t* vertex_ids_{}; | ||
cugraph_type_erased_device_array_t* values_{}; | ||
}; | ||
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} // namespace c_api | ||
} // namespace cugraph |
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/* | ||
* Copyright (c) 2022, 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. | ||
*/ | ||
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#include <cugraph_c/algorithms.h> | ||
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#include <c_api/abstract_functor.hpp> | ||
#include <c_api/centrality_result.hpp> | ||
#include <c_api/graph.hpp> | ||
#include <c_api/resource_handle.hpp> | ||
#include <c_api/utils.hpp> | ||
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#include <cugraph/algorithms.hpp> | ||
#include <cugraph/detail/utility_wrappers.hpp> | ||
#include <cugraph/graph_functions.hpp> | ||
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#include <optional> | ||
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namespace { | ||
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struct eigenvector_centrality_functor : public cugraph::c_api::abstract_functor { | ||
raft::handle_t const& handle_; | ||
cugraph::c_api::cugraph_graph_t* graph_{}; | ||
double epsilon_{}; | ||
size_t max_iterations_{}; | ||
bool do_expensive_check_{}; | ||
cugraph::c_api::cugraph_centrality_result_t* result_{}; | ||
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eigenvector_centrality_functor(cugraph_resource_handle_t const* handle, | ||
cugraph_graph_t* graph, | ||
double epsilon, | ||
size_t max_iterations, | ||
bool do_expensive_check) | ||
: abstract_functor(), | ||
handle_(*reinterpret_cast<cugraph::c_api::cugraph_resource_handle_t const*>(handle)->handle_), | ||
graph_(reinterpret_cast<cugraph::c_api::cugraph_graph_t*>(graph)), | ||
epsilon_(epsilon), | ||
max_iterations_(max_iterations), | ||
do_expensive_check_(do_expensive_check) | ||
{ | ||
} | ||
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template <typename vertex_t, | ||
typename edge_t, | ||
typename weight_t, | ||
bool store_transposed, | ||
bool multi_gpu> | ||
void operator()() | ||
{ | ||
// FIXME: Think about how to handle SG vice MG | ||
if constexpr (!cugraph::is_candidate<vertex_t, edge_t, weight_t>::value) { | ||
unsupported(); | ||
} else { | ||
// Eigenvector Centrality expects store_transposed == true | ||
if constexpr (!store_transposed) { | ||
error_code_ = cugraph::c_api:: | ||
transpose_storage<vertex_t, edge_t, weight_t, store_transposed, multi_gpu>( | ||
handle_, graph_, error_.get()); | ||
if (error_code_ != CUGRAPH_SUCCESS) return; | ||
} | ||
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auto graph = reinterpret_cast<cugraph::graph_t<vertex_t, edge_t, weight_t, true, multi_gpu>*>( | ||
graph_->graph_); | ||
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auto graph_view = graph->view(); | ||
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auto number_map = reinterpret_cast<rmm::device_uvector<vertex_t>*>(graph_->number_map_); | ||
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rmm::device_uvector<weight_t> centralities(graph_view.get_number_of_local_vertices(), | ||
handle_.get_stream()); | ||
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// FIXME: For now we'll call pagerank which returns a similarly formatted thing | ||
cugraph::pagerank<vertex_t, edge_t, weight_t, weight_t, multi_gpu>( | ||
handle_, | ||
graph_view, | ||
std::nullopt, | ||
std::nullopt, | ||
std::nullopt, | ||
std::nullopt, | ||
centralities.data(), | ||
weight_t{0.95}, | ||
static_cast<weight_t>(epsilon_), | ||
max_iterations_, | ||
false, | ||
do_expensive_check_); | ||
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rmm::device_uvector<vertex_t> vertex_ids(graph_view.get_number_of_local_vertices(), | ||
handle_.get_stream()); | ||
raft::copy(vertex_ids.data(), number_map->data(), vertex_ids.size(), handle_.get_stream()); | ||
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result_ = new cugraph::c_api::cugraph_centrality_result_t{ | ||
new cugraph::c_api::cugraph_type_erased_device_array_t(vertex_ids, graph_->vertex_type_), | ||
new cugraph::c_api::cugraph_type_erased_device_array_t(centralities, graph_->weight_type_)}; | ||
} | ||
} | ||
}; | ||
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} // namespace | ||
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extern "C" cugraph_error_code_t cugraph_eigenvector_centrality( | ||
const cugraph_resource_handle_t* handle, | ||
cugraph_graph_t* graph, | ||
double epsilon, | ||
size_t max_iterations, | ||
bool_t do_expensive_check, | ||
cugraph_centrality_result_t** result, | ||
cugraph_error_t** error) | ||
{ | ||
eigenvector_centrality_functor functor( | ||
handle, graph, epsilon, max_iterations, do_expensive_check); | ||
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return cugraph::c_api::run_algorithm(graph, functor, result, error); | ||
} |
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