484 lines
22 KiB
C++
484 lines
22 KiB
C++
// Copyright 2010-2022 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// A pybind11 wrapper for model_builder_helper.
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#include "ortools/linear_solver/wrappers/model_builder_helper.h"
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#include <algorithm>
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#include <complex>
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#include <cstdlib>
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#include <limits>
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#include <optional>
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#include <stdexcept>
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#include <string>
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#include <tuple>
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#include <utility>
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#include <vector>
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#include "Eigen/Core"
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#include "Eigen/SparseCore"
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#include "absl/log/check.h"
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#include "absl/strings/str_cat.h"
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#include "absl/strings/string_view.h"
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#include "ortools/base/logging.h"
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#include "ortools/linear_solver/linear_solver.pb.h"
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#include "ortools/linear_solver/model_exporter.h"
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#include "pybind11/eigen.h"
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#include "pybind11/pybind11.h"
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#include "pybind11/pytypes.h"
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#include "pybind11/stl.h"
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#include "pybind11_protobuf/native_proto_caster.h"
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using ::Eigen::SparseMatrix;
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using ::Eigen::VectorXd;
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using ::operations_research::ModelBuilderHelper;
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using ::operations_research::ModelSolverHelper;
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using ::operations_research::MPConstraintProto;
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using ::operations_research::MPModelExportOptions;
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using ::operations_research::MPModelProto;
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using ::operations_research::MPModelRequest;
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using ::operations_research::MPSolutionResponse;
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using ::operations_research::MPVariableProto;
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using ::operations_research::SolveStatus;
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namespace py = pybind11;
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using ::py::arg;
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const MPModelProto& ToMPModelProto(ModelBuilderHelper* helper) {
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return helper->model();
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}
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// TODO(user): The interface uses serialized protos because of issues building
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// pybind11_protobuf. See
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// https://github.com/protocolbuffers/protobuf/issues/9464. After
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// pybind11_protobuf is working, this workaround can be removed.
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void BuildModelFromSparseData(
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const Eigen::Ref<const VectorXd>& variable_lower_bounds,
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const Eigen::Ref<const VectorXd>& variable_upper_bounds,
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const Eigen::Ref<const VectorXd>& objective_coefficients,
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const Eigen::Ref<const VectorXd>& constraint_lower_bounds,
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const Eigen::Ref<const VectorXd>& constraint_upper_bounds,
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const SparseMatrix<double, Eigen::RowMajor>& constraint_matrix,
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MPModelProto* model_proto) {
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const int num_variables = variable_lower_bounds.size();
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const int num_constraints = constraint_lower_bounds.size();
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if (variable_upper_bounds.size() != num_variables) {
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throw std::invalid_argument(
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absl::StrCat("Invalid size ", variable_upper_bounds.size(),
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" for variable_upper_bounds. Expected: ", num_variables));
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}
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if (objective_coefficients.size() != num_variables) {
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throw std::invalid_argument(absl::StrCat(
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"Invalid size ", objective_coefficients.size(),
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" for linear_objective_coefficients. Expected: ", num_variables));
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}
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if (constraint_upper_bounds.size() != num_constraints) {
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throw std::invalid_argument(absl::StrCat(
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"Invalid size ", constraint_upper_bounds.size(),
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" for constraint_upper_bounds. Expected: ", num_constraints));
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}
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if (constraint_matrix.cols() != num_variables) {
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throw std::invalid_argument(
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absl::StrCat("Invalid number of columns ", constraint_matrix.cols(),
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" in constraint_matrix. Expected: ", num_variables));
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}
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if (constraint_matrix.rows() != num_constraints) {
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throw std::invalid_argument(
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absl::StrCat("Invalid number of rows ", constraint_matrix.rows(),
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" in constraint_matrix. Expected: ", num_constraints));
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}
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for (int i = 0; i < num_variables; ++i) {
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MPVariableProto* variable = model_proto->add_variable();
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variable->set_lower_bound(variable_lower_bounds[i]);
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variable->set_upper_bound(variable_upper_bounds[i]);
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variable->set_objective_coefficient(objective_coefficients[i]);
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}
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for (int row = 0; row < num_constraints; ++row) {
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MPConstraintProto* constraint = model_proto->add_constraint();
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constraint->set_lower_bound(constraint_lower_bounds[row]);
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constraint->set_upper_bound(constraint_upper_bounds[row]);
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for (SparseMatrix<double, Eigen::RowMajor>::InnerIterator it(
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constraint_matrix, row);
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it; ++it) {
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constraint->add_coefficient(it.value());
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constraint->add_var_index(it.col());
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}
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}
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}
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std::vector<std::pair<int, double>> SortedGroupedTerms(
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absl::Span<const int> indices, absl::Span<const double> coefficients) {
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CHECK_EQ(indices.size(), coefficients.size());
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std::vector<std::pair<int, double>> terms;
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terms.reserve(indices.size());
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for (int i = 0; i < indices.size(); ++i) {
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terms.emplace_back(indices[i], coefficients[i]);
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}
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std::sort(
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terms.begin(), terms.end(),
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[](const std::pair<int, double>& a, const std::pair<int, double>& b) {
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if (a.first != b.first) return a.first < b.first;
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if (std::abs(a.second) != std::abs(b.second)) {
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return std::abs(a.second) < std::abs(b.second);
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}
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return a.second < b.second;
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});
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int pos = 0;
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for (int i = 0; i < terms.size(); ++i) {
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const int var = terms[i].first;
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double coeff = terms[i].second;
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while (i + 1 < terms.size() && terms[i + 1].first == var) {
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coeff += terms[i + 1].second;
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++i;
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}
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if (coeff == 0.0) continue;
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terms[pos] = {var, coeff};
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++pos;
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}
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terms.resize(pos);
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return terms;
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}
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PYBIND11_MODULE(model_builder_helper, m) {
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pybind11_protobuf::ImportNativeProtoCasters();
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m.def("to_mpmodel_proto", &ToMPModelProto, arg("helper"));
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py::class_<MPModelExportOptions>(m, "MPModelExportOptions")
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.def(py::init<>())
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.def_readwrite("obfuscate", &MPModelExportOptions::obfuscate)
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.def_readwrite("log_invalid_names",
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&MPModelExportOptions::log_invalid_names)
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.def_readwrite("show_unused_variables",
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&MPModelExportOptions::show_unused_variables)
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.def_readwrite("max_line_length", &MPModelExportOptions::max_line_length);
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py::class_<ModelBuilderHelper>(m, "ModelBuilderHelper")
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.def(py::init<>())
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.def("overwrite_model", &ModelBuilderHelper::OverwriteModel, arg("other_helper"))
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.def("export_to_mps_string", &ModelBuilderHelper::ExportToMpsString,
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arg("options") = MPModelExportOptions())
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.def("export_to_lp_string", &ModelBuilderHelper::ExportToLpString,
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arg("options") = MPModelExportOptions())
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.def("write_model_to_file", &ModelBuilderHelper::WriteModelToFile,
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arg("filename"))
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.def("import_from_mps_string", &ModelBuilderHelper::ImportFromMpsString,
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arg("mps_string"))
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.def("import_from_mps_file", &ModelBuilderHelper::ImportFromMpsFile,
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arg("mps_file"))
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#if defined(USE_LP_PARSER)
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.def("import_from_lp_string", &ModelBuilderHelper::ImportFromLpString,
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arg("lp_string"))
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.def("import_from_lp_file", &ModelBuilderHelper::ImportFromLpFile,
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arg("lp_file"))
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#else
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.def("import_from_lp_string", [](const std::string& lp_string) {
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LOG(INFO) << "Parsing LP string is not compiled in";
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})
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.def("import_from_lp_file", [](const std::string& lp_file) {
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LOG(INFO) << "Parsing LP file is not compiled in";
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})
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#endif
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.def(
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"fill_model_from_sparse_data",
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[](ModelBuilderHelper* helper,
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const Eigen::Ref<const VectorXd>& variable_lower_bounds,
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const Eigen::Ref<const VectorXd>& variable_upper_bounds,
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const Eigen::Ref<const VectorXd>& objective_coefficients,
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const Eigen::Ref<const VectorXd>& constraint_lower_bounds,
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const Eigen::Ref<const VectorXd>& constraint_upper_bounds,
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const SparseMatrix<double, Eigen::RowMajor>& constraint_matrix) {
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BuildModelFromSparseData(
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variable_lower_bounds, variable_upper_bounds,
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objective_coefficients, constraint_lower_bounds,
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constraint_upper_bounds, constraint_matrix,
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helper->mutable_model());
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},
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arg("variable_lower_bound"), arg("variable_upper_bound"),
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arg("objective_coefficients"), arg("constraint_lower_bounds"),
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arg("constraint_upper_bounds"), arg("constraint_matrix"))
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.def("add_var", &ModelBuilderHelper::AddVar)
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.def("add_var_array",
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[](ModelBuilderHelper* helper, std::vector<size_t> shape, double lb,
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double ub, bool is_integral, absl::string_view name_prefix) {
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int size = shape[0];
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for (int i = 1; i < shape.size(); ++i) {
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size *= shape[i];
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}
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py::array_t<int> result(size);
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py::buffer_info info = result.request();
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result.resize(shape);
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auto ptr = static_cast<int*>(info.ptr);
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for (int i = 0; i < size; ++i) {
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const int index = helper->AddVar();
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ptr[i] = index;
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helper->SetVarLowerBound(index, lb);
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helper->SetVarUpperBound(index, ub);
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helper->SetVarIntegrality(index, is_integral);
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if (!name_prefix.empty()) {
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helper->SetVarName(index, absl::StrCat(name_prefix, i));
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}
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}
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return result;
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})
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.def("add_var_array_with_bounds",
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[](ModelBuilderHelper* helper, py::array_t<double> lbs,
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py::array_t<double> ubs, py::array_t<bool> are_integral,
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absl::string_view name_prefix) {
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py::buffer_info buf_lbs = lbs.request();
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py::buffer_info buf_ubs = ubs.request();
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py::buffer_info buf_are_integral = are_integral.request();
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const int size = buf_lbs.size;
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if (size != buf_ubs.size || size != buf_are_integral.size) {
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throw std::runtime_error("Input sizes must match");
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}
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const auto shape = buf_lbs.shape;
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if (shape != buf_ubs.shape || shape != buf_are_integral.shape) {
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throw std::runtime_error("Input shapes must match");
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}
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auto lower_bounds = static_cast<double*>(buf_lbs.ptr);
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auto upper_bounds = static_cast<double*>(buf_ubs.ptr);
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auto integers = static_cast<bool*>(buf_are_integral.ptr);
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py::array_t<int> result(size);
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result.resize(shape);
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py::buffer_info result_info = result.request();
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auto ptr = static_cast<int*>(result_info.ptr);
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for (int i = 0; i < size; ++i) {
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const int index = helper->AddVar();
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ptr[i] = index;
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helper->SetVarLowerBound(index, lower_bounds[i]);
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helper->SetVarUpperBound(index, upper_bounds[i]);
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helper->SetVarIntegrality(index, integers[i]);
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if (!name_prefix.empty()) {
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helper->SetVarName(index, absl::StrCat(name_prefix, i));
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}
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}
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return result;
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})
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.def("set_var_lower_bound", &ModelBuilderHelper::SetVarLowerBound,
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arg("var_index"), arg("lb"))
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.def("set_var_upper_bound", &ModelBuilderHelper::SetVarUpperBound,
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arg("var_index"), arg("ub"))
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.def("set_var_integrality", &ModelBuilderHelper::SetVarIntegrality,
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arg("var_index"), arg("is_integer"))
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.def("set_var_objective_coefficient",
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&ModelBuilderHelper::SetVarObjectiveCoefficient, arg("var_index"),
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arg("coeff"))
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.def("set_objective_coefficients",
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[](ModelBuilderHelper* helper, const std::vector<int>& indices,
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const std::vector<double>& coefficients) {
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for (const auto& [i, c] :
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SortedGroupedTerms(indices, coefficients)) {
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helper->SetVarObjectiveCoefficient(i, c);
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}
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})
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.def("set_var_name", &ModelBuilderHelper::SetVarName, arg("var_index"),
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arg("name"))
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.def("add_linear_constraint", &ModelBuilderHelper::AddLinearConstraint)
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.def("set_constraint_lower_bound",
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&ModelBuilderHelper::SetConstraintLowerBound, arg("ct_index"),
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arg("lb"))
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.def("set_constraint_upper_bound",
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&ModelBuilderHelper::SetConstraintUpperBound, arg("ct_index"),
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arg("ub"))
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.def("add_term_to_constraint", &ModelBuilderHelper::AddConstraintTerm,
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arg("ct_index"), arg("var_index"), arg("coeff"))
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.def("add_terms_to_constraint",
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[](ModelBuilderHelper* helper, int ct_index,
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const std::vector<int>& indices,
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const std::vector<double>& coefficients) {
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for (const auto& [i, c] :
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SortedGroupedTerms(indices, coefficients)) {
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helper->AddConstraintTerm(ct_index, i, c);
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}
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})
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.def("safe_add_term_to_constraint",
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&ModelBuilderHelper::SafeAddConstraintTerm, arg("ct_index"),
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arg("var_index"), arg("coeff"))
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.def("set_constraint_name", &ModelBuilderHelper::SetConstraintName,
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arg("ct_index"), arg("name"))
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.def("set_constraint_coefficient",
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&ModelBuilderHelper::SetConstraintCoefficient, arg("ct_index"),
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arg("var_index"), arg("coeff"))
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.def("num_variables", &ModelBuilderHelper::num_variables)
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.def("var_lower_bound", &ModelBuilderHelper::VarLowerBound,
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arg("var_index"))
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.def("var_upper_bound", &ModelBuilderHelper::VarUpperBound,
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arg("var_index"))
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.def("var_is_integral", &ModelBuilderHelper::VarIsIntegral,
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arg("var_index"))
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.def("var_objective_coefficient",
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&ModelBuilderHelper::VarObjectiveCoefficient, arg("var_index"))
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.def("var_name", &ModelBuilderHelper::VarName, arg("var_index"))
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.def("num_constraints", &ModelBuilderHelper::num_constraints)
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.def("constraint_lower_bound", &ModelBuilderHelper::ConstraintLowerBound,
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arg("ct_index"))
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.def("constraint_upper_bound", &ModelBuilderHelper::ConstraintUpperBound,
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arg("ct_index"))
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.def("constraint_name", &ModelBuilderHelper::ConstraintName,
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arg("ct_index"))
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.def("constraint_var_indices", &ModelBuilderHelper::ConstraintVarIndices,
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arg("ct_index"))
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.def("constraint_coefficients",
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&ModelBuilderHelper::ConstraintCoefficients, arg("ct_index"))
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.def("name", &ModelBuilderHelper::name)
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.def("set_name", &ModelBuilderHelper::SetName, arg("name"))
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.def("clear_objective", &ModelBuilderHelper::ClearObjective)
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.def("maximize", &ModelBuilderHelper::maximize)
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.def("set_maximize", &ModelBuilderHelper::SetMaximize, arg("maximize"))
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.def("set_objective_offset", &ModelBuilderHelper::SetObjectiveOffset,
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arg("offset"))
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.def("objective_offset", &ModelBuilderHelper::ObjectiveOffset)
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.def("sort_and_regroup_terms",
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[](ModelBuilderHelper* helper, py::array_t<int> indices,
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py::array_t<double> coefficients) {
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const std::vector<std::pair<int, double>> terms =
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SortedGroupedTerms(indices, coefficients);
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std::vector<int> sorted_indices;
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std::vector<double> sorted_coefficients;
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sorted_indices.reserve(terms.size());
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sorted_coefficients.reserve(terms.size());
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for (const auto& [i, c] : terms) {
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sorted_indices.push_back(i);
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sorted_coefficients.push_back(c);
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}
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return std::make_pair(sorted_indices, sorted_coefficients);
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});
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py::enum_<SolveStatus>(m, "SolveStatus")
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.value("OPTIMAL", SolveStatus::OPTIMAL)
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.value("FEASIBLE", SolveStatus::FEASIBLE)
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.value("INFEASIBLE", SolveStatus::INFEASIBLE)
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.value("UNBOUNDED", SolveStatus::UNBOUNDED)
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.value("ABNORMAL", SolveStatus::ABNORMAL)
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.value("NOT_SOLVED", SolveStatus::NOT_SOLVED)
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.value("MODEL_IS_VALID", SolveStatus::MODEL_IS_VALID)
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.value("CANCELLED_BY_USER", SolveStatus::CANCELLED_BY_USER)
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.value("UNKNOWN_STATUS", SolveStatus::UNKNOWN_STATUS)
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.value("MODEL_INVALID", SolveStatus::MODEL_INVALID)
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.value("INVALID_SOLVER_PARAMETERS",
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SolveStatus::INVALID_SOLVER_PARAMETERS)
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.value("SOLVER_TYPE_UNAVAILABLE", SolveStatus::SOLVER_TYPE_UNAVAILABLE)
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.value("INCOMPATIBLE_OPTIONS", SolveStatus::INCOMPATIBLE_OPTIONS)
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.export_values();
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py::class_<ModelSolverHelper>(m, "ModelSolverHelper")
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.def(py::init<const std::string&>())
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.def("solver_is_supported", &ModelSolverHelper::SolverIsSupported)
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.def("solve", &ModelSolverHelper::Solve, arg("model"),
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// The GIL is released during the solve to allow Python threads to do
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// other things in parallel, e.g., log and interrupt.
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py::call_guard<py::gil_scoped_release>())
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.def("solve_serialized_request",
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[](ModelSolverHelper* solver, absl::string_view request_str) {
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std::string result;
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{
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// The GIL is released during the solve to allow Python threads
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// to do other things in parallel, e.g., log and interrupt.
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py::gil_scoped_release release;
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MPModelRequest request;
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if (!request.ParseFromString(std::string(request_str))) {
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throw std::invalid_argument(
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"Unable to parse request as MPModelRequest.");
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}
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std::optional<MPSolutionResponse> solution =
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solver->SolveRequest(request);
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if (solution.has_value()) {
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result = solution.value().SerializeAsString();
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}
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}
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return py::bytes(result);
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})
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.def("interrupt_solve", &ModelSolverHelper::InterruptSolve,
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"Returns true if the interrupt signal was correctly sent, that is, "
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"if the underlying solver supports it.")
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.def("set_log_callback", &ModelSolverHelper::SetLogCallback)
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.def("clear_log_callback", &ModelSolverHelper::ClearLogCallback)
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.def("set_time_limit_in_seconds",
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&ModelSolverHelper::SetTimeLimitInSeconds, arg("limit"))
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.def("set_solver_specific_parameters",
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&ModelSolverHelper::SetSolverSpecificParameters,
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arg("solver_specific_parameters"))
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.def("enable_output", &ModelSolverHelper::EnableOutput, arg("output"))
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.def("has_solution", &ModelSolverHelper::has_solution)
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.def("has_response", &ModelSolverHelper::has_response)
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.def("response", &ModelSolverHelper::response)
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.def("status", &ModelSolverHelper::status)
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.def("status_string", &ModelSolverHelper::status_string)
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.def("wall_time", &ModelSolverHelper::wall_time)
|
|
.def("user_time", &ModelSolverHelper::user_time)
|
|
.def("objective_value", &ModelSolverHelper::objective_value)
|
|
.def("best_objective_bound", &ModelSolverHelper::best_objective_bound)
|
|
.def("var_value", &ModelSolverHelper::variable_value, arg("var_index"))
|
|
.def("reduced_cost", &ModelSolverHelper::reduced_cost, arg("var_index"))
|
|
.def("dual_value", &ModelSolverHelper::dual_value, arg("ct_index"))
|
|
.def("activity", &ModelSolverHelper::activity, arg("ct_index"))
|
|
.def("variable_values",
|
|
[](const ModelSolverHelper& helper) {
|
|
if (!helper.has_response()) {
|
|
throw std::logic_error(
|
|
"Accessing a solution value when none has been found.");
|
|
}
|
|
const MPSolutionResponse& response = helper.response();
|
|
Eigen::VectorXd vec(response.variable_value_size());
|
|
for (int i = 0; i < response.variable_value_size(); ++i) {
|
|
vec[i] = response.variable_value(i);
|
|
}
|
|
return vec;
|
|
})
|
|
.def("expression_value",
|
|
[](const ModelSolverHelper& helper, const std::vector<int>& indices,
|
|
const std::vector<double>& coefficients, double constant) {
|
|
if (!helper.has_response()) {
|
|
throw std::logic_error(
|
|
"Accessing a solution value when none has been found.");
|
|
}
|
|
const MPSolutionResponse& response = helper.response();
|
|
for (int i = 0; i < indices.size(); ++i) {
|
|
constant +=
|
|
response.variable_value(indices[i]) * coefficients[i];
|
|
}
|
|
return constant;
|
|
})
|
|
.def("reduced_costs",
|
|
[](const ModelSolverHelper& helper) {
|
|
if (!helper.has_response()) {
|
|
throw std::logic_error(
|
|
"Accessing a solution value when none has been found.");
|
|
}
|
|
const MPSolutionResponse& response = helper.response();
|
|
Eigen::VectorXd vec(response.reduced_cost_size());
|
|
for (int i = 0; i < response.reduced_cost_size(); ++i) {
|
|
vec[i] = response.reduced_cost(i);
|
|
}
|
|
return vec;
|
|
})
|
|
.def("dual_values", [](const ModelSolverHelper& helper) {
|
|
if (!helper.has_response()) {
|
|
throw std::logic_error(
|
|
"Accessing a solution value when none has been found.");
|
|
}
|
|
const MPSolutionResponse& response = helper.response();
|
|
Eigen::VectorXd vec(response.dual_value_size());
|
|
for (int i = 0; i < response.dual_value_size(); ++i) {
|
|
vec[i] = response.dual_value(i);
|
|
}
|
|
return vec;
|
|
});
|
|
}
|