-
Notifications
You must be signed in to change notification settings - Fork 71
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
AssertionError: Rendering dt (0.03333333333333333) must be a multiple of physics dt (0.01) #12
Comments
in config.yaml, set num physics_frequency=30 or 60 |
Thank you, it works |
Hello,my friends! I have the same problem as you, and I set num physics_frequency=30. But after that, I have new problem as follow:
[INFO] [omnigibson.simulator] ---------- Welcome to OmniGibson! ----------
2024-11-08 08:42:32 [8,165ms] [Warning] [carb] [Plugin: omni.sensors.tiled.plugin] Module /home/dawn/anaconda3/envs/omnigibson/lib/python3.10/site-packages/isaacsim/extscache/omni.sensors.tiled-0.0.4+106.0.0.lx64.r/bin/libomni.sensors.tiled.plugin.so remained loaded after unload request Current thread 0x00007f5637910740 (most recent call first): Extension modules: mkl._mklinit, mkl._py_mkl_service, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, torch._C, torch._C._dynamo.autograd_compiler, torch._C._dynamo.eval_frame, torch._C._dynamo.guards, torch._C._dynamo.utils, torch._C._fft, torch._C._linalg, torch._C._nested, torch._C._nn, torch._C._sparse, torch._C._special, scipy._lib._ccallback_c, yaml._yaml, numba.core.typeconv._typeconv, numba._helperlib, numba._dynfunc, numba._dispatcher, numba.core.runtime._nrt_python, numba.np.ufunc._internal, numba.experimental.jitclass._box, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg.cython_lapack, scipy.linalg._cythonized_array_utils, scipy.linalg._solve_toeplitz, scipy.linalg._decomp_lu_cython, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg._matfuncs_expm, scipy.linalg._decomp_update, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.sparse.linalg._propack._spropack, scipy.sparse.linalg._propack._dpropack, scipy.sparse.linalg._propack._cpropack, scipy.sparse.linalg._propack._zpropack, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, scipy.spatial._ckdtree, scipy._lib.messagestream, scipy.spatial._qhull, scipy.spatial._voronoi, scipy.spatial._distance_wrap, scipy.spatial._hausdorff, scipy.special._ufuncs_cxx, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, _moduleTNC, scipy.optimize._moduleTNC, scipy.optimize._cobyla, scipy.optimize._slsqp, scipy.optimize._minpack, scipy.optimize._lsq.givens_elimination, scipy.optimize._zeros, scipy.optimize._highs.cython.src._highs_wrapper, scipy.optimize._highs._highs_wrapper, scipy.optimize._highs.cython.src._highs_constants, scipy.optimize._highs._highs_constants, scipy.linalg._interpolative, scipy.optimize._bglu_dense, scipy.optimize._lsap, scipy.optimize._direct, psutil._psutil_linux, psutil._psutil_posix, PIL._imaging, markupsafe._speedups, sklearn.__check_build._check_build, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.interpolate._fitpack, scipy.interpolate._dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.interpolate._rbfinterp_pythran, scipy.interpolate._rgi_cython, scipy.special.cython_special, scipy.stats._stats, scipy.stats._biasedurn, scipy.stats._levy_stable.levyst, scipy.stats._stats_pythran, scipy._lib._uarray._uarray, scipy.stats._ansari_swilk_statistics, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._mvn, scipy.stats._rcont.rcont, scipy.stats._unuran.unuran_wrapper, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.strptime, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.lib, pandas._libs.ops, pandas._libs.hashing, pandas._libs.arrays, pandas._libs.tslib, pandas._libs.sparse, pandas._libs.internals, pandas._libs.indexing, pandas._libs.index, pandas._libs.writers, pandas._libs.join, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.groupby, pandas._libs.json, pandas._libs.parsers, pandas._libs.testing, sklearn.utils._isfinite, sklearn.utils.sparsefuncs_fast, sklearn.utils.murmurhash, sklearn.utils._openmp_helpers, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.preprocessing._csr_polynomial_expansion, sklearn.preprocessing._target_encoder_fast, sklearn.metrics._dist_metrics, sklearn.metrics._pairwise_distances_reduction._datasets_pair, sklearn.utils._cython_blas, sklearn.metrics._pairwise_distances_reduction._base, sklearn.metrics._pairwise_distances_reduction._middle_term_computer, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction._argkmin, sklearn.metrics._pairwise_distances_reduction._argkmin_classmode, sklearn.utils._vector_sentinel, sklearn.metrics._pairwise_distances_reduction._radius_neighbors, sklearn.metrics._pairwise_distances_reduction._radius_neighbors_classmode, sklearn.metrics._pairwise_fast, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.utils.arrayfuncs, sklearn.utils._random, sklearn.utils._seq_dataset, sklearn.linear_model._cd_fast, _loss, sklearn._loss._loss, sklearn.svm._liblinear, sklearn.svm._libsvm, sklearn.svm._libsvm_sparse, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, sklearn.decomposition._online_lda_fast, sklearn.decomposition._cdnmf_fast, h5py._errors, h5py.defs, h5py._objects, h5py.h5, h5py.utils, h5py.h5t, h5py.h5s, h5py.h5ac, h5py.h5p, h5py.h5r, h5py._proxy, h5py._conv, h5py.h5z, h5py.h5a, h5py.h5d, h5py.h5ds, h5py.h5g, h5py.h5i, h5py.h5f, h5py.h5fd, h5py.h5pl, h5py.h5o, h5py.h5l, h5py._selector, _cffi_backend, kiwisolver._cext, sklearn.utils._fast_dict, sklearn.cluster._hierarchical_fast, sklearn.cluster._k_means_common, sklearn.cluster._k_means_elkan, sklearn.cluster._k_means_lloyd, sklearn.cluster._k_means_minibatch, sklearn.cluster._dbscan_inner, sklearn.cluster._hdbscan._tree, sklearn.cluster._hdbscan._linkage, sklearn.cluster._hdbscan._reachability, sklearn._isotonic, sklearn.tree._utils, sklearn.tree._tree, sklearn.tree._splitter, sklearn.tree._criterion, sklearn.neighbors._quad_tree, sklearn.manifold._barnes_hut_tsne, sklearn.manifold._utils, _brotli, gmpy2.gmpy2, omni.mdl.pymdlsdk._pymdlsdk, PIL._imagingft, osqp._osqp, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, scipy.io.matlab._mio_utils, scipy.io.matlab._streams, scipy.io.matlab._mio5_utils (total: 259) I will appreciate it if you could answer that! |
in og_scene_file_pen.json, line 897, set "scale":[2.0,2.0,2.0] |
sorry, it doesn't work. |
I also meet this question too,after set like this,I can see the scene,but program crash soon。 2024-12-06 06:11:43 [15,275ms] [Warning] [omni.syntheticdata.plugin] SdRenderVarPtr missing valid input renderVar LdrColorSDhost |
Hello, I also met the same question, but after set like this, I met a new question, the terminal output indicates the following warnings and an error traceback:
I wonder how I should do to solve this problem, thank you! |
I met the same problem. Could I ask you whether you have solved this problem? Thanks :) |
@VincentWanghh @Lilac-cc @BateCheaterDemon @Benxiaogu. Use this repository: https://github.com/Bailey-24/Rekep |
Sorry, it doesn't work out neither. |
Sorry, I haven't solved it yet. If you work it out, could you please share the solution with me? Thank you.
…------------------ 原始邮件 ------------------
发件人: "huangwl18/ReKep" ***@***.***>;
发送时间: 2024年12月27日(星期五) 中午1:50
***@***.***>;
***@***.******@***.***>;
主题: Re: [huangwl18/ReKep] AssertionError: Rendering dt (0.03333333333333333) must be a multiple of physics dt (0.01) (Issue #12)
in config.yaml, set num physics_frequency=30 or 60
Hello, I also met the same question, but after set like this, I met a new question, the terminal output indicates the following warnings and an error traceback:
[13.073s] [ext: omni.particle.system.bundle-105.1.0] startup Traceback (most recent call last): File "/root/autodl-tmp/ReKep/main.py", line 379, in <module> main = Main(scene_file, visualize=args.visualize) File "/root/autodl-tmp/ReKep/main.py", line 40, in __init__ self.env = ReKepOGEnv(global_config['env'], scene_file, verbose=False) File "/root/autodl-tmp/ReKep/environment.py", line 69, in __init__ self.og_env = og.Environment(dict(scene=self.config['scene'], robots=[self.config['robot']['robot_config']], env=self.config['og_sim'])) File "/root/miniconda3/envs/omnigibson/lib/python3.10/site-packages/omnigibson/utils/python_utils.py", line 93, in wrapper func(*values.args, **values.kwargs) File "/root/miniconda3/envs/omnigibson/lib/python3.10/site-packages/omnigibson/envs/env_base.py", line 103, in __init__ og.launch( File "/root/miniconda3/envs/omnigibson/lib/python3.10/site-packages/omnigibson/simulator.py", line 1780, in _launch_simulator Simulator(*args, **kwargs) File "/root/miniconda3/envs/omnigibson/lib/python3.10/site-packages/omnigibson/simulator.py", line 295, in __init__ self._validate_dts(physics_dt, rendering_dt, sim_step_dt) File "/root/miniconda3/envs/omnigibson/lib/python3.10/site-packages/omnigibson/simulator.py", line 524, in _validate_dts assert sim_step_dt == rendering_dt, ( AssertionError: Simulation step dt (0.06666666666666667) must be equal to rendering dt (0.03333333333333333) when gm.HEADLESS is set!
I wonder how I should do to solve this problem, thank you!
I met the same problem. Could I ask you whether you have solved this problem? Thanks :)
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you commented.Message ID: ***@***.***>
|
Thank you. It works! |
Was anyone able to get this to work with headless mode? Receiving |
I'm experiencing a crash when executing the following command:
The terminal output indicates the following warnings and an error traceback:
The text was updated successfully, but these errors were encountered: