Expose CorrDevBuilder to Python and add example use of the CorrDist f…

…unctions from python.

PiperOrigin-RevId: 572869884
Change-Id: Id5075edd8a234e4a838926152d22d4d0248f3558

open_spiel/algorithms/cfr.h

@@ -218,6 +218,11 @@ class CFRSolverBase {
     return std::make_shared<CFRCurrentPolicy>(info_states_, nullptr);
   }
 
+  TabularPolicy TabularCurrentPolicy() const {
+    CFRCurrentPolicy policy(info_states_, nullptr);
+    return policy.AsTabular();
+  }
+
   CFRInfoStateValuesTable& InfoStateValuesTable() { return info_states_; }
 
   // See comments above CFRInfoStateValues::Serialize(double_precision) for

open_spiel/python/algorithms/cfr_test.py

@@ -272,5 +272,58 @@ def test_cpp_algorithms_identical_to_python_algorithm(self, game, cpp_class,
     self.assertEqual(cpp_expl, python_expl)
 
 
+class CorrDistTest(absltest.TestCase):
+  """Test some of the correlation device distances functions in C++.
+
+  These functions are analogues to NashConv for various forms of correlated
+  equilibria.
+  """
+
+  def test_cce_dist_kuhn_3p_cpp(self):
+    game = pyspiel.load_game("kuhn_poker(players=3)")
+    solver = pyspiel.CFRSolver(game)  # C++ solver
+    strategies = []
+    corr_dist_values = []
+    for _ in range(10):
+      solver.evaluate_and_update_policy()
+      strategies.append(solver.tabular_current_policy())
+      corr_dev = pyspiel.uniform_correlation_device(strategies)
+      cce_dist_info = pyspiel.cce_dist(game, corr_dev)
+      corr_dist_values.append(cce_dist_info.dist_value)
+    self.assertLess(corr_dist_values[-1], corr_dist_values[0])
+
+  def test_cce_dist_kuhn_3p(self):
+    game = pyspiel.load_game("kuhn_poker(players=3)")
+    solver = cfr._CFRSolver(game,
+                            regret_matching_plus=False,
+                            linear_averaging=False,
+                            alternating_updates=True)
+    strategies = []
+    corr_dist_values = []
+    for _ in range(10):
+      solver.evaluate_and_update_policy()
+      # Convert the policy to a pyspiel.TabularPolicy, needed by the CorrDist
+      # functions on the C++ side.
+      strategies.append(policy.python_policy_to_pyspiel_policy(
+          solver.current_policy()))
+      corr_dev = pyspiel.uniform_correlation_device(strategies)
+      cce_dist_info = pyspiel.cce_dist(game, corr_dev)
+      corr_dist_values.append(cce_dist_info.dist_value)
+    self.assertLess(corr_dist_values[-1], corr_dist_values[0])
+
+  def test_cce_dist_sheriff_cpp(self):
+    game = pyspiel.load_game("sheriff")
+    solver = pyspiel.CFRSolver(game)  # C++ solver
+    strategies = []
+    corr_dist_values = []
+    for _ in range(3):
+      solver.evaluate_and_update_policy()
+      strategies.append(solver.tabular_current_policy())
+      corr_dev = pyspiel.uniform_correlation_device(strategies)
+      cce_dist_info = pyspiel.cce_dist(game, corr_dev)
+      corr_dist_values.append(cce_dist_info.dist_value)
+    self.assertLess(corr_dist_values[-1], corr_dist_values[0])
+
+
 if __name__ == "__main__":
   absltest.main()

open_spiel/python/pybind11/algorithms_corr_dist.cc

@@ -14,15 +14,18 @@
 
 #include "open_spiel/python/pybind11/algorithms_corr_dist.h"
 
-// Python bindings for trajectories.h
+#include <memory>
 
 #include "open_spiel/algorithms/corr_dev_builder.h"
 #include "open_spiel/algorithms/corr_dist.h"
-#include "open_spiel/python/pybind11/pybind11.h"
+#include "open_spiel/spiel.h"
+#include "pybind11/include/pybind11/cast.h"
+#include "pybind11/include/pybind11/pybind11.h"
 
 namespace open_spiel {
 namespace py = ::pybind11;
 
+using open_spiel::algorithms::CorrDevBuilder;
 using open_spiel::algorithms::CorrDistInfo;
 using open_spiel::algorithms::CorrelationDevice;
 
@@ -50,6 +53,20 @@ void init_pyspiel_algorithms_corr_dist(py::module& m) {
       .def_readonly("conditional_best_response_policies",
                     &CorrDistInfo::conditional_best_response_policies);
 
+  py::class_<CorrDevBuilder> corr_dev_builder(m, "CorrDevBuilder");
+  corr_dev_builder.def(py::init<int>(), py::arg("seed") = 0)
+      .def("add_deterministic_joint_policy",
+           &CorrDevBuilder::AddDeterminsticJointPolicy,
+           py::arg("policy"), py::arg("weight") = 1.0)
+      .def("add_sampled_joint_policy",
+           &CorrDevBuilder::AddSampledJointPolicy,
+           py::arg("policy"), py::arg("num_samples"), py::arg("weight") = 1.0)
+      .def("add_mixed_joint_policy",
+            &CorrDevBuilder::AddMixedJointPolicy,
+            py::arg("policy"),
+            py::arg("weight") = 1.0)
+      .def("get_correlation_device", &CorrDevBuilder::GetCorrelationDevice);
+
   m.def(
       "cce_dist",
       [](std::shared_ptr<const Game> game,

open_spiel/python/pybind11/policy.cc

@@ -228,6 +228,8 @@ void init_pyspiel_policy(py::module& m) {
       .def("average_policy", &open_spiel::algorithms::CFRSolver::AveragePolicy)
       .def("tabular_average_policy",
            &open_spiel::algorithms::CFRSolver::TabularAveragePolicy)
+      .def("tabular_current_policy",
+           &open_spiel::algorithms::CFRSolver::TabularCurrentPolicy)
       .def(py::pickle(
           [](const open_spiel::algorithms::CFRSolver& solver) {  // __getstate__
             return solver.Serialize();