Segmentation fault similar to issue 8410

[forestbat]

What is your issue?

This is my crash report and I think it's similar to #8410 :

 Fatal Python error: Segmentation fault

Thread 0x00007f4ff8daf700 (most recent call first):
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/concurrent/futures/thread.py", line 81 in _worker
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 982 in run
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1045 in _bootstrap_inner
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1002 in _bootstrap
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydev_bundle/pydev_monkey.py", line 817 in __call__

Thread 0x00007f505a78f700 (most recent call first):
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/selectors.py", line 468 in select
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers-pro/pydevd_asyncio/pydevd_nest_asyncio.py", line 263 in _run_once
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers-pro/pydevd_asyncio/pydevd_nest_asyncio.py", line 218 in run_forever
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 982 in run
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1045 in _bootstrap_inner
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1002 in _bootstrap
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydev_bundle/pydev_monkey.py", line 817 in __call__

Thread 0x00007f5157fff700 (most recent call first):
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 331 in wait
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 629 in wait
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/pydevd.py", line 157 in _on_run
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydevd_bundle/pydevd_comm.py", line 219 in run
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1045 in _bootstrap_inner
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1002 in _bootstrap

Thread 0x00007f515c818700 (most recent call first):
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydevd_bundle/pydevd_comm.py", line 293 in _on_run
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydevd_bundle/pydevd_comm.py", line 219 in run
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1045 in _bootstrap_inner
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1002 in _bootstrap

Thread 0x00007f515d019700 (most recent call first):
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 331 in wait
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/queue.py", line 180 in get
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydevd_bundle/pydevd_comm.py", line 370 in _on_run
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydevd_bundle/pydevd_comm.py", line 219 in run
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1045 in _bootstrap_inner
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/threading.py", line 1002 in _bootstrap

Current thread 0x00007f516fb65740 (most recent call first):
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/file_manager.py", line 217 in _acquire_with_cache_info
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/file_manager.py", line 199 in acquire_context
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/contextlib.py", line 137 in __enter__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/netCDF4_.py", line 411 in _acquire
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/netCDF4_.py", line 417 in ds
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/netCDF4_.py", line 355 in __init__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/netCDF4_.py", line 408 in open
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/netCDF4_.py", line 645 in open_dataset
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/xarray/backends/api.py", line 571 in open_dataset
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/hydrodatasource/reader/access_fs.py", line 92 in read_valid_data
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/hydrodatasource/reader/access_fs.py", line 20 in spec_path
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/hydrodatasource/reader/data_source.py", line 438 in read_MP
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_scalers.py", line 293 in mean_prcp
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_scalers.py", line 414 in get_data_obs
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_scalers.py", line 487 in load_data
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_scalers.py", line 104 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 279 in _normalize
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 620 in _normalize
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 261 in _load_data
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 119 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 613 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 678 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/datasets/data_sets.py", line 762 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/trainers/deep_hydro.py", line 227 in make_dataset
  File "/home/wangyang1/torchhydro/torchhydro/trainers/deep_hydro.py", line 152 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/trainers/deep_hydro.py", line 782 in __init__
  File "/home/wangyang1/torchhydro/torchhydro/trainers/trainer.py", line 80 in _get_deep_hydro
  File "/home/wangyang1/torchhydro/torchhydro/trainers/trainer.py", line 63 in train_and_evaluate
  File "/home/wangyang1/torchhydro/experiments/train_with_era5land_gnn.py", line 54 in test_run_model
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/python.py", line 159 in pytest_pyfunc_call
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_callers.py", line 103 in _multicall
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_manager.py", line 120 in _hookexec
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_hooks.py", line 513 in __call__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/python.py", line 1627 in runtest
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/runner.py", line 174 in pytest_runtest_call
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_callers.py", line 103 in _multicall
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_manager.py", line 120 in _hookexec
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_hooks.py", line 513 in __call__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/runner.py", line 242 in <lambda>
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/runner.py", line 341 in from_call
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/runner.py", line 241 in call_and_report
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/runner.py", line 132 in runtestprotocol
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/runner.py", line 113 in pytest_runtest_protocol
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_callers.py", line 103 in _multicall
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_manager.py", line 120 in _hookexec
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_hooks.py", line 513 in __call__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/main.py", line 362 in pytest_runtestloop
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_callers.py", line 103 in _multicall
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_manager.py", line 120 in _hookexec
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_hooks.py", line 513 in __call__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/main.py", line 337 in _main
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/main.py", line 283 in wrap_session
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/main.py", line 330 in pytest_cmdline_main
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_callers.py", line 103 in _multicall
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_manager.py", line 120 in _hookexec
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/pluggy/_hooks.py", line 513 in __call__
  File "/home/jiaxuwu/.conda/envs/forest-minio/lib/python3.11/site-packages/_pytest/config/__init__.py", line 175 in main
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pycharm/_jb_pytest_runner.py", line 75 in <module>
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18 in execfile
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/pydevd.py", line 1546 in _exec
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/pydevd.py", line 1539 in run
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/pydevd.py", line 2229 in main
  File "/home/wangyang1/.local/share/JetBrains/IntelliJIdea2024.1/python/helpers/pydev/pydevd.py", line 2247 in <module>

Extension modules: 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, matplotlib._c_internal_utils, PIL._imaging, matplotlib._path, kiwisolver._cext, _pydevd_bundle.pydevd_cython, _pydevd_bundle_ext.pydevd_cython, pyarrow.lib, 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, pyarrow._compute, pandas._libs.ops, bottleneck.move, bottleneck.nonreduce, bottleneck.nonreduce_axis, bottleneck.reduce, 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, yaml._yaml, _brotli, charset_normalizer.md, cytoolz.utils, cytoolz.itertoolz, cytoolz.functoolz, cytoolz.dicttoolz, cytoolz.recipes, ujson, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, _cffi_backend, frozenlist._frozenlist, sklearn.__check_build._check_build, scipy._lib._ccallback_c, 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, lz4._version, lz4.frame._frame, psutil._psutil_linux, psutil._psutil_posix, 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._cdflib, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, scipy.optimize._minpack2, 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, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.special.cython_special, scipy.stats._stats, scipy.stats.beta_ufunc, scipy.stats._boost.beta_ufunc, scipy.stats.binom_ufunc, scipy.stats._boost.binom_ufunc, scipy.stats.nbinom_ufunc, scipy.stats._boost.nbinom_ufunc, scipy.stats.hypergeom_ufunc, scipy.stats._boost.hypergeom_ufunc, scipy.stats.ncf_ufunc, scipy.stats._boost.ncf_ufunc, scipy.stats.ncx2_ufunc, scipy.stats._boost.ncx2_ufunc, scipy.stats.nct_ufunc, scipy.stats._boost.nct_ufunc, scipy.stats.skewnorm_ufunc, scipy.stats._boost.skewnorm_ufunc, scipy.stats.invgauss_ufunc, scipy.stats._boost.invgauss_ufunc, scipy.interpolate._fitpack, scipy.interpolate.dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.interpolate._rbfinterp_pythran, scipy.interpolate._rgi_cython, 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, sklearn.utils._isfinite, sklearn.utils.murmurhash, sklearn.utils._openmp_helpers, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.utils.sparsefuncs_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.utils._random, torch._C, torch._C._fft, torch._C._linalg, torch._C._nested, torch._C._nn, torch._C._sparse, torch._C._special, dgl._ffi._cy3.core, pyarrow._parquet, pyarrow._fs, pyarrow._azurefs, pyarrow._hdfs, pyarrow._gcsfs, pyarrow._s3fs, scipy.io.matlab._mio_utils, scipy.io.matlab._streams, scipy.io.matlab._mio5_utils, shapely.lib, shapely._geos, shapely._geometry_helpers, pyproj._compat, pyproj._datadir, pyproj._network, pyproj._geod, pyproj.list, pyproj._crs, pyproj.database, pyproj._transformer, pyproj._sync, igraph._igraph, matplotlib._image, cftime._cftime, netCDF4._netCDF4, markupsafe._speedups, cupy_backends.cuda._softlink, cupy_backends.cuda.api._runtime_enum, cupy_backends.cuda.api.runtime, cupy._util, cupy.cuda.device, fastrlock.rlock, cupy.cuda.memory_hook, cupy_backends.cuda.stream, cupy.cuda.graph, cupy.cuda.stream, cupy_backends.cuda.api._driver_enum, cupy_backends.cuda.api.driver, cupy.cuda.memory, cupy._core.internal, cupy._core._carray, cupy.cuda.texture, cupy.cuda.function, cupy_backends.cuda.libs.nvrtc, cupy.cuda.pinned_memory, cupy.cuda.common, cupy.cuda.cub, cupy_backends.cuda.libs.nvtx, cupy.cuda.thrust, cupy._core._dtype, cupy._core._scalar, cupy._core._accelerator, cupy._core._memory_range, cupy._core._fusion_thread_local, cupy._core._kernel, cupy._core._routines_manipulation, cupy._core._routines_binary, cupy._core._optimize_config, cupy._core._cub_reduction, cupy._core._reduction, cupy._core._routines_math, cupy._core._routines_indexing, cupy._core._routines_linalg, cupy._core._routines_logic, cupy._core._routines_sorting, cupy._core._routines_statistics, cupy._core.dlpack, cupy._core.flags, cupy._core.core, cupy._core._fusion_variable, cupy._core._fusion_trace, cupy._core._fusion_kernel, cupy._core.new_fusion, cupy._core.fusion, cupy._core.raw, cupy.fft._cache, cupy.fft._callback, cupy.random._bit_generator, cupy.lib._polynomial, scipy.fftpack.convolve, psycopg2._psycopg, numcodecs.compat_ext, numcodecs.blosc, numcodecs.zstd, numcodecs.lz4, numcodecs._shuffle, msgpack._cmsgpack, numcodecs.jenkins, numcodecs.vlen, numcodecs.fletcher32, 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, google._upb._message, scipy.cluster._vq, scipy.cluster._hierarchy, scipy.cluster._optimal_leaf_ordering, numba.core.typeconv._typeconv, numba._helperlib, numba._dynfunc, numba._dispatcher, numba.core.runtime._nrt_python, numba.np.ufunc._internal, numba.experimental.jitclass._box, 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.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.utils.arrayfuncs, sklearn.utils._seq_dataset, sklearn.linear_model._cd_fast, 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, 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, sklearn.ensemble._gradient_boosting, sklearn.ensemble._hist_gradient_boosting.common, sklearn.ensemble._hist_gradient_boosting._gradient_boosting, sklearn.ensemble._hist_gradient_boosting._binning, sklearn.ensemble._hist_gradient_boosting._bitset, sklearn.ensemble._hist_gradient_boosting.histogram, sklearn.ensemble._hist_gradient_boosting._predictor, sklearn.ensemble._hist_gradient_boosting.splitting, sklearn.ensemble._hist_gradient_boosting.utils, shap._cext, shap._cext_gpu, sklearn.datasets._svmlight_format_fast, sklearn.feature_extraction._hashing_fast, rasterio._version, rasterio._err, rasterio._filepath, rasterio._env, rasterio._transform, rasterio._base, rasterio.crs, rasterio._features, rasterio._warp, rasterio._io, tornado.speedups, lz4.block._block (total: 403)

进程已结束，退出代码为 139 (interrupted by signal 11:SIGSEGV)

I have downgraded netCDF4 to 1.6.0 but the problem still occurs.
Do you have any other solutions, rather than converting netcdf files to other formats?

[max-sixty]

Please fill out a bug report template with an MCVE, thank you