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//
// 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.
// Tests for engine/engine_solver.c
#include <algorithm>
#include <cstdlib>
#include <string>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include <mujoco/mujoco.h>
#include "test/fixture.h"
namespace mujoco {
namespace {
using ::testing::DoubleNear;
using ::testing::NotNull;
using ::std::abs;
using ::std::max;
using SolverTest = MujocoTest;
static const char* const kModelPath =
"testdata/model.xml";
// compare accelerations produced by CG solver with and without islands
TEST_F(SolverTest, IslandsEquivalent) {
const std::string xml_path = GetTestDataFilePath(kModelPath);
char error[1024];
mjModel* model = mj_loadXML(xml_path.c_str(), nullptr, error, sizeof(error));
ASSERT_THAT(model, NotNull()) << error;
model->opt.solver = mjSOL_CG; // use CG solver
model->opt.jacobian = mjJAC_SPARSE; // use sparse
model->opt.tolerance = 0; // set tolerance to 0
model->opt.ls_tolerance = 0; // set ls_tolerance to 0
int nv = model->nv;
int state_size = mj_stateSize(model, mjSTATE_INTEGRATION);
mjtNum* state = (mjtNum*) mju_malloc(sizeof(mjtNum)*state_size);
mjData* data_island = mj_makeData(model);
mjData* data_noisland = mj_makeData(model);
// Below are 3 tolerances associated with 3 different iteration counts,
// they are only moderately tight, 2x higher than x86-64 failure on Linux,
// i.e. in that case the test fails with rtol smaller than {5e-3, 5e-4, 5e-5}.
// The point of this test is to show that CG convergence is actually not very
// precise, simply changing whether islands are used changes the solution by
// quite a lot, even at high iteration count and zero {ls_}tolerance.
// Increasing the iteration count higher than 60 does not improve convergence.
constexpr int kNumTol = 3;
mjtNum maxiter[kNumTol] = {30, 40, 60};
mjtNum rtol[kNumTol] = {1e-2, 1e-3, 1e-4};
for (int i = 0; i < kNumTol; ++i) {
model->opt.iterations = maxiter[i];
model->opt.ls_iterations = maxiter[i];
for (bool coldstart : {true, false}) {
mj_resetDataKeyframe(model, data_noisland, 0);
if (coldstart) {
model->opt.disableflags |= mjDSBL_WARMSTART;
} else {
model->opt.disableflags &= ~mjDSBL_WARMSTART;
}
while (data_noisland->time < .1) {
mj_getState(model, data_noisland, state, mjSTATE_INTEGRATION);
mj_setState(model, data_island, state, mjSTATE_INTEGRATION);
model->opt.enableflags |= mjENBL_ISLAND; // enable islands
mj_forward(model, data_island);
model->opt.enableflags &= ~mjENBL_ISLAND; // disable islands
mj_forward(model, data_noisland);
auto time = std::to_string(data_noisland->time);
for (int j = 0; j < nv; j++) {
// increase tolerance for large elements
mjtNum scale = 0.5 * max(2.0, abs(data_noisland->qacc[j]) +
abs(data_island->qacc[j]));
EXPECT_THAT(data_noisland->qacc[j],
DoubleNear(data_island->qacc[j], scale * rtol[i]))
<< "time: " << time << '\n'
<< "dof: " << j << '\n'
<< "maxiter: " << maxiter[i] << '\n'
<< "rtol: " << scale * rtol[i];
}
mj_step(model, data_noisland);
}
}
}
mj_deleteData(data_noisland);
mj_deleteData(data_island);
mju_free(state);
mj_deleteModel(model);
}
// compare accelerations produced by CG solver with and without islands
TEST_F(SolverTest, IslandsEquivalentForward) {
const std::string xml_path = GetTestDataFilePath(kModelPath);
char error[1024];
mjModel* model = mj_loadXML(xml_path.c_str(), nullptr, error, sizeof(error));
ASSERT_THAT(model, NotNull()) << error;
model->opt.solver = mjSOL_CG; // use CG solver
model->opt.tolerance = 0; // set tolerance to 0
model->opt.ls_tolerance = 0; // set ls_tolerance to 0
mjtNum rtol = 3e-6;
mjData* data_island = mj_makeData(model);
mjData* data_noisland = mj_makeData(model);
for (bool coldstart : {true, false}) {
mj_resetDataKeyframe(model, data_island, 0);
mj_resetDataKeyframe(model, data_noisland, 0);
if (coldstart) {
model->opt.disableflags |= mjDSBL_WARMSTART;
} else {
model->opt.disableflags &= ~mjDSBL_WARMSTART;
}
model->opt.enableflags &= ~mjENBL_ISLAND; // disable islands
mj_forward(model, data_noisland);
model->opt.enableflags |= mjENBL_ISLAND; // enable islands
mj_forward(model, data_island);
for (int j = 0; j < model->nv; j++) {
mjtNum scale = 0.5 * max(2.0, abs(data_noisland->qacc[j]) +
abs(data_island->qacc[j]));
EXPECT_THAT(data_noisland->qacc[j],
DoubleNear(data_island->qacc[j], scale * rtol))
<< "dof: " << j << '\n'
<< "rtol: " << scale * rtol;
}
}
mj_deleteData(data_noisland);
mj_deleteData(data_island);
mj_deleteModel(model);
}
} // namespace
} // namespace mujoco
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