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Mujoco_WASM/python/mujoco/rollout.cc
T
Yuval Tassa a0f014593b Support float32 in mujoco.rollout Python wrapper and tests.
- Update rollout.py to use mujoco.MJTNUM_DTYPE instead of np.float64.
- Update rollout_test.py to use DTYPE for all state/control/sensor arrays to avoid copies and type mismatches.

PiperOrigin-RevId: 928539946
Change-Id: Iee2250c049de799cb0e23ffe5558fe6eea8b3fd8
2026-06-08 06:59:22 -07:00

364 lines
12 KiB
C++

// Copyright 2022 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 <algorithm>
#include <cstddef>
#include <iostream>
#include <memory>
#include <optional>
#include <sstream>
#include <vector>
#include <mujoco/mujoco.h>
#include "errors.h"
#include "raw.h"
#include "structs.h"
#include "threadpool.h"
#include <pybind11/buffer_info.h>
#include <pybind11/numpy.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace mujoco::python {
namespace {
namespace py = ::pybind11;
using PyCArray = py::array_t<mjtNum, py::array::c_style>;
// NOLINTBEGIN(whitespace/line_length)
const auto rollout_init_doc = R"(
Construct a rollout object containing a thread pool for parallel rollouts.
input arguments (optional):
nthread integer, number of threads in pool
if zero, this pool is not started and rollouts run on the calling thread
)";
const auto rollout_doc = R"(
Roll out batch of trajectories from initial states, get resulting states and sensor values.
input arguments (required):
model list of homogenous MjModel instances of length nbatch
data list of compatible MjData instances of length nthread
nstep integer, number of steps to be taken for each trajectory
control_spec specification of controls, ncontrol = mj_stateSize(m, control_spec)
state0 (nbatch x nstate) nbatch initial state arrays, where
nstate = mj_stateSize(m, mjSTATE_FULLPHYSICS)
input arguments (optional):
warmstart0 (nbatch x nv) nbatch qacc_warmstart arrays
control (nbatch x nstep x ncontrol) nbatch trajectories of nstep controls
output arguments (optional):
state (nbatch x nstep x nstate) nbatch nstep states
sensordata (nbatch x nstep x nsendordata) nbatch trajectories of nstep sensordata arrays
chunk_size integer, determines threadpool chunk size. If unspecified, the default is
chunk_size = max(1, nbatch / (nthread * 10))
)";
// C-style rollout function, assumes all arguments are valid
// all input fields of d are initialised, contents at call time do not matter
// after returning, d will contain the last step of the last rollout
void _unsafe_rollout(std::vector<const mjModel*>& m, mjData* d, int start_roll,
int end_roll, int nstep, unsigned int control_spec,
const mjtNum* state0, const mjtNum* warmstart0,
const mjtNum* control, mjtNum* state, mjtNum* sensordata) {
// sizes
size_t nstate = static_cast<size_t>(mj_stateSize(m[0], mjSTATE_FULLPHYSICS));
size_t ncontrol = static_cast<size_t>(mj_stateSize(m[0], control_spec));
size_t nv = static_cast<size_t>(m[0]->nv);
int nbody = m[0]->nbody, neq = m[0]->neq;
size_t nsensordata = static_cast<size_t>(m[0]->nsensordata);
// clear user inputs if unspecified
if (!(control_spec & mjSTATE_CTRL)) {
mju_zero(d->ctrl, m[0]->nu);
}
if (!(control_spec & mjSTATE_QFRC_APPLIED)) {
mju_zero(d->qfrc_applied, nv);
}
if (!(control_spec & mjSTATE_XFRC_APPLIED)) {
mju_zero(d->xfrc_applied, 6*nbody);
}
// loop over rollouts
for (size_t r = start_roll; r < end_roll; r++) {
// clear user inputs if unspecified
if (!(control_spec & mjSTATE_MOCAP_POS)) {
for (int i = 0; i < nbody; i++) {
int id = m[r]->body_mocapid[i];
if (id >= 0) mju_copy3(d->mocap_pos+3*id, m[r]->body_pos+3*i);
}
}
if (!(control_spec & mjSTATE_MOCAP_QUAT)) {
for (int i = 0; i < nbody; i++) {
int id = m[r]->body_mocapid[i];
if (id >= 0) mju_copy4(d->mocap_quat+4*id, m[r]->body_quat+4*i);
}
}
if (!(control_spec & mjSTATE_EQ_ACTIVE)) {
for (int i = 0; i < neq; i++) {
d->eq_active[i] = m[r]->eq_active0[i];
}
}
// set initial state
mj_setState(m[r], d, state0 + r*nstate, mjSTATE_FULLPHYSICS);
// set warmstart accelerations
if (warmstart0) {
mju_copy(d->qacc_warmstart, warmstart0 + r*nv, nv);
} else {
mju_zero(d->qacc_warmstart, nv);
}
// clear warning counters
for (int i = 0; i < mjNWARNING; i++) {
d->warning[i].number = 0;
}
// roll out trajectory
for (size_t t = 0; t < nstep; t++) {
// check for warnings
bool nwarning = false;
for (int i = 0; i < mjNWARNING; i++) {
if (d->warning[i].number) {
nwarning = true;
break;
}
}
// if any warnings, fill remaining outputs with current outputs, break
if (nwarning) {
for (; t < nstep; t++) {
size_t step = r*static_cast<size_t>(nstep) + t;
if (state) {
mj_getState(m[r], d, state + step*nstate, mjSTATE_FULLPHYSICS);
}
if (sensordata) {
mju_copy(sensordata + step*nsensordata, d->sensordata, nsensordata);
}
}
break;
}
size_t step = r*static_cast<size_t>(nstep) + t;
// controls
if (control) {
mj_setState(m[r], d, control + step*ncontrol, control_spec);
}
// step
mj_step(m[r], d);
// copy out new state
if (state) {
mj_getState(m[r], d, state + step*nstate, mjSTATE_FULLPHYSICS);
}
// copy out sensor values
if (sensordata) {
mju_copy(sensordata + step*nsensordata, d->sensordata, nsensordata);
}
}
}
}
// C-style threaded version of _unsafe_rollout
void _unsafe_rollout_threaded(std::vector<const mjModel*>& m,
std::vector<mjData*>& d, int nbatch, int nstep,
unsigned int control_spec, const mjtNum* state0,
const mjtNum* warmstart0, const mjtNum* control,
mjtNum* state, mjtNum* sensordata,
ThreadPool* pool, int chunk_size) {
int nfulljobs = nbatch / chunk_size;
int chunk_remainder = nbatch % chunk_size;
int njobs = (chunk_remainder > 0) ? nfulljobs + 1 : nfulljobs;
// Reset the pool counter
pool->ResetCount();
// schedule all jobs of full (chunk) size
for (int j = 0; j < nfulljobs; j++) {
auto task = [=, &m, &d](void) {
int id = pool->WorkerId();
_unsafe_rollout(m, d[id], j*chunk_size, (j+1)*chunk_size,
nstep, control_spec, state0, warmstart0, control, state, sensordata);
};
pool->Schedule(task);
}
// schedule any remaining jobs of size < chunk_size
if (chunk_remainder > 0) {
auto task = [=, &m, &d](void) {
_unsafe_rollout(m, d[pool->WorkerId()], nfulljobs*chunk_size,
nfulljobs*chunk_size+chunk_remainder,
nstep, control_spec, state0, warmstart0, control, state, sensordata);
};
pool->Schedule(task);
}
// wait for counter to increment up to number of jobs submitted by this thread
pool->WaitCount(njobs);
}
// NOLINTEND(whitespace/line_length)
// check size of optional argument to rollout(), return raw pointer
mjtNum* get_array_ptr(std::optional<const py::array_t<mjtNum>> arg,
const char* name, int nbatch, int nstep, int dim) {
// if empty return nullptr
if (!arg.has_value()) {
return nullptr;
}
// get info
py::buffer_info info = arg->request();
// check size
size_t expected_size = static_cast<size_t>(nbatch) *
static_cast<size_t>(nstep) * static_cast<size_t>(dim);
if (info.size != expected_size) {
std::ostringstream msg;
msg << name << ".size should be " << expected_size << ", got " << info.size;
throw py::value_error(msg.str());
}
return static_cast<mjtNum*>(info.ptr);
}
class Rollout {
public:
Rollout(int nthread) : nthread_(nthread) {
if (this->nthread_ > 0) {
this->pool_ = std::make_shared<ThreadPool>(this->nthread_);
}
}
void rollout(py::list m, py::list d, int nstep, unsigned int control_spec,
const PyCArray state0, std::optional<const PyCArray> warmstart0,
std::optional<const PyCArray> control,
std::optional<const PyCArray> state,
std::optional<const PyCArray> sensordata,
std::optional<int> chunk_size) {
// get raw pointers
int nbatch = state0.shape(0);
std::vector<const raw::MjModel*> model_ptrs(nbatch);
for (int r = 0; r < nbatch; r++) {
model_ptrs[r] = m[r].cast<const MjModelWrapper*>()->get();
}
// check length d and nthread are consistent
if (py::len(d) == 0) {
std::ostringstream msg;
msg << "The list of data instances is empty";
throw py::value_error(msg.str());
} else if (this->nthread_ == 0 && py::len(d) > 1) {
std::ostringstream msg;
msg << "More than one data instance passed but "
<< "rollout is configured to run on main thread";
throw py::value_error(msg.str());
} else if (this->nthread_ > 0 && this->nthread_ != py::len(d)) {
std::ostringstream msg;
msg << "Length of data: " << py::len(d)
<< " not equal to nthread: " << this->nthread_;
throw py::value_error(msg.str());
}
std::vector<raw::MjData*> data_ptrs(py::len(d));
for (int t = 0; t < py::len(d); t++) {
data_ptrs[t] = d[t].cast<MjDataWrapper*>()->get();
}
// check that some steps need to be taken, return if not
if (nstep < 1) {
return;
}
// get sizes
int nstate = mj_stateSize(model_ptrs[0], mjSTATE_FULLPHYSICS);
int ncontrol = mj_stateSize(model_ptrs[0], control_spec);
mjtNum* state0_ptr = get_array_ptr(state0, "state0", nbatch, 1, nstate);
mjtNum* warmstart0_ptr =
get_array_ptr(warmstart0, "warmstart0", nbatch, 1, model_ptrs[0]->nv);
mjtNum* control_ptr =
get_array_ptr(control, "control", nbatch, nstep, ncontrol);
mjtNum* state_ptr = get_array_ptr(state, "state", nbatch, nstep, nstate);
mjtNum* sensordata_ptr = get_array_ptr(sensordata, "sensordata", nbatch,
nstep, model_ptrs[0]->nsensordata);
// perform rollouts
{
// release the GIL
py::gil_scoped_release no_gil;
// call unsafe rollout function, multi or single threaded
if (this->nthread_ > 0 && nbatch > 1) {
int chunk_size_final = 1;
if (!chunk_size.has_value()) {
chunk_size_final = std::max(1, nbatch / (10 * this->nthread_));
} else {
chunk_size_final = *chunk_size;
}
InterceptMjErrors(_unsafe_rollout_threaded)(
model_ptrs, data_ptrs, nbatch, nstep, control_spec, state0_ptr,
warmstart0_ptr, control_ptr, state_ptr, sensordata_ptr,
this->pool_.get(), chunk_size_final);
} else {
InterceptMjErrors(_unsafe_rollout)(
model_ptrs, data_ptrs[0], 0, nbatch, nstep, control_spec,
state0_ptr, warmstart0_ptr, control_ptr, state_ptr, sensordata_ptr);
}
}
}
private:
int nthread_;
std::shared_ptr<ThreadPool> pool_;
};
PYBIND11_MODULE(_rollout, pymodule) {
namespace py = ::pybind11;
py::class_<Rollout>(pymodule, "Rollout")
.def(
py::init([](int nthread) {
return std::make_unique<Rollout>(nthread);
}),
py::kw_only(),
py::arg("nthread"),
py::doc(rollout_init_doc))
.def(
"rollout",
&Rollout::rollout,
py::arg("model"),
py::arg("data"),
py::arg("nstep"),
py::arg("control_spec"),
py::arg("state0"),
py::arg("warmstart0") = py::none(),
py::arg("control") = py::none(),
py::arg("state") = py::none(),
py::arg("sensordata") = py::none(),
py::arg("chunk_size") = py::none(),
py::doc(rollout_doc));
}
} // namespace
} // namespace mujoco::python