Alessio Quaglino
c17375fa32
PiperOrigin-RevId: 490239351 Change-Id: Id73c101672e5b974f16b6b4da3aae757a657de15
112 lines
3.6 KiB
C++
112 lines
3.6 KiB
C++
// Copyright 2021 DeepMind Technologies Limited
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//
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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 benchmark which steps various models without rendering, and measures speed.
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#include <array>
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#include <benchmark/benchmark.h>
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#include <gmock/gmock.h>
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#include <gtest/gtest.h>
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#include <absl/base/attributes.h>
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#include <mujoco/mjdata.h>
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#include <mujoco/mjmodel.h>
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#include <mujoco/mujoco.h>
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#include "test/fixture.h"
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namespace mujoco {
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namespace {
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// number of steps to roll out before benhmarking
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static const int kNumWarmupSteps = 500;
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// number of steps to benchmark
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static const int kNumBenchmarkSteps = 50;
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// copy array into vector
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std::vector<mjtNum> AsVector(const mjtNum* array, int n) {
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return std::vector<mjtNum>(array, array + n);
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}
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static void run_step_benchmark(const mjModel* model, benchmark::State& state) {
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mjData* data = mj_makeData(model);
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// compute noise
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int nsteps = kNumWarmupSteps+kNumBenchmarkSteps;
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std::vector<mjtNum> ctrl = GetCtrlNoise(model, nsteps);
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// warm-up rollout to get a typcal state
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for (int i=0; i < kNumWarmupSteps; i++) {
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mju_copy(data->ctrl, ctrl.data()+model->nu*i, model->nu);
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mj_step(model, data);
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}
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// save state
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std::vector<mjtNum> qpos = AsVector(data->qpos, model->nq);
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std::vector<mjtNum> qvel = AsVector(data->qvel, model->nv);
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std::vector<mjtNum> act = AsVector(data->act, model->na);
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std::vector<mjtNum> warmstart = AsVector(data->qacc_warmstart, model->nv);
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// reset state, benchmark subsequent kNumBenchmarkSteps steps
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while (state.KeepRunningBatch(kNumBenchmarkSteps)) {
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mju_copy(data->qpos, qpos.data(), model->nq);
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mju_copy(data->qvel, qvel.data(), model->nv);
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mju_copy(data->act, act.data(), model->na);
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mju_copy(data->qacc_warmstart, warmstart.data(), model->nv);
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for (int i=kNumWarmupSteps; i < nsteps; i++) {
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mju_copy(data->ctrl, ctrl.data()+model->nu*i, model->nu);
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mj_step(model, data);
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}
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}
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// finalize
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mj_deleteData(data);
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state.SetItemsProcessed(state.iterations());
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}
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// Use ABSL_ATTRIBUTE_NO_TAIL_CALL to make sure the benchmark functions appear
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// separately in CPU profiles (and don't get replaced with raw calls to
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// run_step_benchmark).
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void ABSL_ATTRIBUTE_NO_TAIL_CALL BM_StepCloth(benchmark::State& state) {
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MujocoErrorTestGuard guard;
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static mjModel* model = LoadModelFromPath("composite/cloth.xml");
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run_step_benchmark(model, state);
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}
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BENCHMARK(BM_StepCloth);
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void ABSL_ATTRIBUTE_NO_TAIL_CALL BM_StepFlag(benchmark::State& state) {
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MujocoErrorTestGuard guard;
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static mjModel* model = LoadModelFromPath("flag/flag.xml");
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run_step_benchmark(model, state);
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}
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BENCHMARK(BM_StepFlag);
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void ABSL_ATTRIBUTE_NO_TAIL_CALL BM_StepHumanoid(benchmark::State& state) {
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MujocoErrorTestGuard guard;
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static mjModel* model = LoadModelFromPath("humanoid/humanoid.xml");
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run_step_benchmark(model, state);
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}
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BENCHMARK(BM_StepHumanoid);
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void ABSL_ATTRIBUTE_NO_TAIL_CALL BM_StepHumanoid100(benchmark::State& state) {
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MujocoErrorTestGuard guard;
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static mjModel* model = LoadModelFromPath("humanoid100/humanoid100.xml");
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run_step_benchmark(model, state);
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}
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BENCHMARK(BM_StepHumanoid100);
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} // namespace
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} // namespace mujoco
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