Files
Mujoco_WASM/sample/derivative.cc
T
Saran Tunyasuvunakool 1913a02b40 Initial open sourcing of MuJoCo.
PiperOrigin-RevId: 450374687
Change-Id: Ie3225a46ce095fc28ae8e63c326a640261f562bb
2022-05-23 01:08:49 -07:00

440 lines
12 KiB
C++

// Copyright 2021 DeepMind Technologies Limited
//
// 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.
#include <cstdio>
#include <cstring>
#include <mujoco/mujoco.h>
// enable compilation with and without OpenMP support
#if defined(_OPENMP)
#include <omp.h>
#else
// omp timer replacement
#include <chrono>
double omp_get_wtime(void) {
static std::chrono::system_clock::time_point _start = std::chrono::system_clock::now();
std::chrono::duration<double> elapsed = std::chrono::system_clock::now() - _start;
return elapsed.count();
}
// omp functions used below
void omp_set_dynamic(int) {}
void omp_set_num_threads(int) {}
int omp_get_num_procs(void) {
return 1;
}
#endif
// gloval variables: internal
const int MAXTHREAD = 64; // maximum number of threads allowed
const int MAXEPOCH = 100; // maximum number of epochs
int isforward = 0; // dynamics mode: forward or inverse
mjtNum* deriv = 0; // dynamics derivatives (6*nv*nv):
// dinv/dpos, dinv/dvel, dinv/dacc, dacc/dpos, dacc/dvel, dacc/dfrc
// global variables: user-defined, with defaults
int nthread = 0; // number of parallel threads (default set later)
int niter = 30; // fixed number of solver iterations for finite-differencing
int nwarmup = 3; // center point repetitions to improve warmstart
int nepoch = 20; // number of timing epochs
int nstep = 500; // number of simulation steps per epoch
double eps = 1e-6; // finite-difference epsilon
// worker function for parallel finite-difference computation of derivatives
void worker(const mjModel* m, const mjData* dmain, mjData* d, int id) {
int nv = m->nv;
// allocate stack space for result at center
mjMARKSTACK;
mjtNum* center = mj_stackAlloc(d, nv);
mjtNum* warmstart = mj_stackAlloc(d, nv);
// prepare static schedule: range of derivative columns to be computed by this thread
int chunk = (m->nv + nthread-1) / nthread;
int istart = id * chunk;
int iend = mjMIN(istart + chunk, m->nv);
// copy state and control from dmain to thread-specific d
d->time = dmain->time;
mju_copy(d->qpos, dmain->qpos, m->nq);
mju_copy(d->qvel, dmain->qvel, m->nv);
mju_copy(d->qacc, dmain->qacc, m->nv);
mju_copy(d->qacc_warmstart, dmain->qacc_warmstart, m->nv);
mju_copy(d->qfrc_applied, dmain->qfrc_applied, m->nv);
mju_copy(d->xfrc_applied, dmain->xfrc_applied, 6*m->nbody);
mju_copy(d->ctrl, dmain->ctrl, m->nu);
// run full computation at center point (usually faster than copying dmain)
if (isforward) {
mj_forward(m, d);
// extra solver iterations to improve warmstart (qacc) at center point
for (int rep=1; rep<nwarmup; rep++) {
mj_forwardSkip(m, d, mjSTAGE_VEL, 1);
}
} else {
mj_inverse(m, d);
}
// select output from forward or inverse dynamics
mjtNum* output = (isforward ? d->qacc : d->qfrc_inverse);
// save output for center point and warmstart (needed in forward only)
mju_copy(center, output, nv);
mju_copy(warmstart, d->qacc_warmstart, nv);
// select target vector and original vector for force or acceleration derivative
mjtNum* target = (isforward ? d->qfrc_applied : d->qacc);
const mjtNum* original = (isforward ? dmain->qfrc_applied : dmain->qacc);
// finite-difference over force or acceleration: skip = mjSTAGE_VEL
for (int i=istart; i<iend; i++) {
// perturb selected target
target[i] += eps;
// evaluate dynamics, with center warmstart
if (isforward) {
mju_copy(d->qacc_warmstart, warmstart, m->nv);
mj_forwardSkip(m, d, mjSTAGE_VEL, 1);
} else {
mj_inverseSkip(m, d, mjSTAGE_VEL, 1);
}
// undo perturbation
target[i] = original[i];
// compute column i of derivative 2
for (int j=0; j<nv; j++) {
deriv[(3*isforward+2)*nv*nv + i + j*nv] = (output[j] - center[j])/eps;
}
}
// finite-difference over velocity: skip = mjSTAGE_POS
for (int i=istart; i<iend; i++) {
// perturb velocity
d->qvel[i] += eps;
// evaluate dynamics, with center warmstart
if (isforward) {
mju_copy(d->qacc_warmstart, warmstart, m->nv);
mj_forwardSkip(m, d, mjSTAGE_POS, 1);
} else {
mj_inverseSkip(m, d, mjSTAGE_POS, 1);
}
// undo perturbation
d->qvel[i] = dmain->qvel[i];
// compute column i of derivative 1
for (int j=0; j<nv; j++) {
deriv[(3*isforward+1)*nv*nv + i + j*nv] = (output[j] - center[j])/eps;
}
}
// finite-difference over position: skip = mjSTAGE_NONE
for (int i=istart; i<iend; i++) {
// get joint id for this dof
int jid = m->dof_jntid[i];
// get quaternion address and dof position within quaternion (-1: not in quaternion)
int quatadr = -1, dofpos = 0;
if (m->jnt_type[jid]==mjJNT_BALL) {
quatadr = m->jnt_qposadr[jid];
dofpos = i - m->jnt_dofadr[jid];
} else if (m->jnt_type[jid]==mjJNT_FREE && i>=m->jnt_dofadr[jid]+3) {
quatadr = m->jnt_qposadr[jid] + 3;
dofpos = i - m->jnt_dofadr[jid] - 3;
}
// apply quaternion or simple perturbation
if (quatadr>=0) {
mjtNum angvel[3] = {0, 0, 0};
angvel[dofpos] = eps;
mju_quatIntegrate(d->qpos+quatadr, angvel, 1);
} else {
d->qpos[m->jnt_qposadr[jid] + i - m->jnt_dofadr[jid]] += eps;
}
// evaluate dynamics, with center warmstart
if (isforward) {
mju_copy(d->qacc_warmstart, warmstart, m->nv);
mj_forwardSkip(m, d, mjSTAGE_NONE, 1);
} else {
mj_inverseSkip(m, d, mjSTAGE_NONE, 1);
}
// undo perturbation
mju_copy(d->qpos, dmain->qpos, m->nq);
// compute column i of derivative 0
for (int j=0; j<nv; j++) {
deriv[(3*isforward+0)*nv*nv + i + j*nv] = (output[j] - center[j])/eps;
}
}
mjFREESTACK;
}
// compute relative L1 norm of residual
double relnorm(mjtNum* residual, mjtNum* base, int n) {
mjtNum L1res = 0, L1base = 0;
for (int i=0; i<n; i++) {
L1res += mju_abs(residual[i]);
L1base += mju_abs(base[i]);
}
return (double) mju_log10(mju_max(mjMINVAL, L1res/mju_max(mjMINVAL, L1base)));
}
// names of residuals for accuracy check
const char* accuracy[8] = {
"G2*F2 - I ",
"G2 - G2' ",
"G1 - G1' ",
"F2 - F2' ",
"G1 + G2*F1",
"G0 + G2*F0",
"F1 + F2*G1",
"F0 + F2*G0"
};
// check accuracy of derivatives using known mathematical identities
void checkderiv(const mjModel* m, mjData* d, mjtNum error[7]) {
int nv = m->nv;
// allocate space
mjMARKSTACK;
mjtNum* mat = mj_stackAlloc(d, nv*nv);
// get pointers to derivative matrices
mjtNum* G0 = deriv; // dinv/dpos
mjtNum* G1 = deriv + nv*nv; // dinv/dvel
mjtNum* G2 = deriv + 2*nv*nv; // dinv/dacc
mjtNum* F0 = deriv + 3*nv*nv; // dacc/dpos
mjtNum* F1 = deriv + 4*nv*nv; // dacc/dvel
mjtNum* F2 = deriv + 5*nv*nv; // dacc/dfrc
// G2*F2 - I
mju_mulMatMat(mat, G2, F2, nv, nv, nv);
for (int i=0; i<nv; i++) {
mat[i*(nv+1)] -= 1;
}
error[0] = relnorm(mat, G2, nv*nv);
// G2 - G2'
mju_transpose(mat, G2, nv, nv);
mju_sub(mat, mat, G2, nv*nv);
error[1] = relnorm(mat, G2, nv*nv);
// G1 - G1'
mju_transpose(mat, G1, nv, nv);
mju_sub(mat, mat, G1, nv*nv);
error[2] = relnorm(mat, G1, nv*nv);
// F2 - F2'
mju_transpose(mat, F2, nv, nv);
mju_sub(mat, mat, F2, nv*nv);
error[3] = relnorm(mat, F2, nv*nv);
// G1 + G2*F1
mju_mulMatMat(mat, G2, F1, nv, nv, nv);
mju_addTo(mat, G1, nv*nv);
error[4] = relnorm(mat, G1, nv*nv);
// G0 + G2*F0
mju_mulMatMat(mat, G2, F0, nv, nv, nv);
mju_addTo(mat, G0, nv*nv);
error[5] = relnorm(mat, G0, nv*nv);
// F1 + F2*G1
mju_mulMatMat(mat, F2, G1, nv, nv, nv);
mju_addTo(mat, F1, nv*nv);
error[6] = relnorm(mat, F1, nv*nv);
// F0 + F2*G0
mju_mulMatMat(mat, F2, G0, nv, nv, nv);
mju_addTo(mat, F0, nv*nv);
error[7] = relnorm(mat, F0, nv*nv);
mjFREESTACK;
}
// main function
int main(int argc, char** argv) {
// print help if not enough arguments
if (argc<2) {
std::printf("\n Arguments: modelfile [nthread niter nwarmup nepoch nstep eps]\n\n");
return 1;
}
// default nthread = number of logical cores (usually optimal)
nthread = omp_get_num_procs();
// get numeric command-line arguments
if (argc>2) {
std::sscanf(argv[2], "%d", &nthread);
}
if (argc>3) {
std::sscanf(argv[3], "%d", &niter);
}
if (argc>4) {
std::sscanf(argv[4], "%d", &nwarmup);
}
if (argc>5) {
std::sscanf(argv[5], "%d", &nepoch);
}
if (argc>6) {
std::sscanf(argv[6], "%d", &nstep);
}
if (argc>7) {
std::sscanf(argv[7], "%lf", &eps);
}
// check number of threads
if (nthread<1 || nthread>MAXTHREAD) {
std::printf("nthread must be between 1 and %d\n", MAXTHREAD);
return 1;
}
// check number of epochs
if (nepoch<1 || nepoch>MAXEPOCH) {
std::printf("nepoch must be between 1 and %d\n", MAXEPOCH);
return 1;
}
// load model
mjModel* m = 0;
if (std::strlen(argv[1])>4 && !std::strcmp(argv[1]+std::strlen(argv[1])-4, ".mjb")) {
m = mj_loadModel(argv[1], NULL);
} else {
m = mj_loadXML(argv[1], NULL, NULL, 0);
}
if (!m) {
std::printf("Could not load modelfile '%s'\n", argv[1]);
return 1;
}
// print arguments
#if defined(_OPENMP)
std::printf("\nnthread : %d (OpenMP)\n", nthread);
#else
std::printf("\nnthread : %d (serial)\n", nthread);
#endif
std::printf("niter : %d\n", niter);
std::printf("nwarmup : %d\n", nwarmup);
std::printf("nepoch : %d\n", nepoch);
std::printf("nstep : %d\n", nstep);
std::printf("eps : %g\n\n", eps);
// make mjData: main, per-thread
mjData* dmain = mj_makeData(m);
mjData* d[MAXTHREAD];
for (int n=0; n<nthread; n++) {
d[n] = mj_makeData(m);
}
// allocate derivatives
deriv = (mjtNum*) mju_malloc(6*sizeof(mjtNum)*m->nv*m->nv);
// set up OpenMP (if not enabled, this does nothing)
omp_set_dynamic(0);
omp_set_num_threads(nthread);
// save solver options
int save_iterations = m->opt.iterations;
mjtNum save_tolerance = m->opt.tolerance;
// allocate statistics
int nefc = 0;
double cputm[MAXEPOCH][2];
mjtNum error[MAXEPOCH][8];
// run epochs, collect statistics
for (int epoch=0; epoch<nepoch; epoch++) {
// set solver options for main simulation
m->opt.iterations = save_iterations;
m->opt.tolerance = save_tolerance;
// advance main simulation for nstep
for (int i=0; i<nstep; i++) {
mj_step(m, dmain);
}
// count number of active constraints
nefc += dmain->nefc;
// set solver options for finite differences
m->opt.iterations = niter;
m->opt.tolerance = 0;
// test forward and inverse
for (isforward=0; isforward<2; isforward++) {
// start timer
double starttm = omp_get_wtime();
// run worker threads in parallel if OpenMP is enabled
#pragma omp parallel for schedule(static)
for (int n=0; n<nthread; n++) {
worker(m, dmain, d[n], n);
}
// record duration in ms
cputm[epoch][isforward] = 1000*(omp_get_wtime() - starttm);
}
// check derivatives
checkderiv(m, d[0], error[epoch]);
}
// compute statistics
double mcputm[2] = {0, 0}, merror[8] = {0, 0, 0, 0, 0, 0, 0, 0};
for (int epoch=0; epoch<nepoch; epoch++) {
mcputm[0] += cputm[epoch][0];
mcputm[1] += cputm[epoch][1];
for (int ie=0; ie<8; ie++) {
merror[ie] += error[epoch][ie];
}
}
// print sizes, timing, accuracy
std::printf("sizes : nv %d, nefc %d\n\n", m->nv, nefc/nepoch);
std::printf("inverse : %.2f ms\n", mcputm[0]/nepoch);
std::printf("forward : %.2f ms\n\n", mcputm[1]/nepoch);
std::printf("accuracy: log10(residual L1 relnorm)\n");
std::printf("------------------------------------\n");
for (int ie=0; ie<8; ie++) {
std::printf(" %s : %.2g\n", accuracy[ie], merror[ie]/nepoch);
}
std::printf("\n");
// shut down
mju_free(deriv);
mj_deleteData(dmain);
for (int n=0; n<nthread; n++) {
mj_deleteData(d[n]);
}
mj_deleteModel(m);
return 0;
}