I was trying to test https://github.com/NVIDIA/apex/tree/master/apex/contrib/openfold_triton with triton but encountered this error and cannot find the solution anywhere. It'd be great if I could get some pointers to check which part I did wrong.
Fatal Python error: Aborted
Current thread 0x00007f7325dfa280 (most recent call first):
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/triton/compiler.py", line 1006 in ttgir_to_llir
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/triton/compiler.py", line 1554 in <lambda>
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/triton/compiler.py", line 1621 in compile
File "<string>", line 41 in _attention_core
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 199 in run
File "/home/rui/code/test-fold-dev/test-fold/ops/attention/triton/mha_fwd.py", line 476 in attn_core_fwd
File "/home/rui/code/test-fold-dev/tests/unit/ops/attention/flash_attention_test.py", line 18 in test_flash_attention_fwd
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/python.py", line 194 in pytest_pyfunc_call
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_callers.py", line 77 in _multicall
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_manager.py", line 115 in _hookexec
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_hooks.py", line 493 in __call__
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/python.py", line 1792 in runtest
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 169 in pytest_runtest_call
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_callers.py", line 77 in _multicall
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_manager.py", line 115 in _hookexec
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_hooks.py", line 493 in __call__
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 262 in <lambda>
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 341 in from_call
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 261 in call_runtest_hook
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 222 in call_and_report
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 133 in runtestprotocol
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/runner.py", line 114 in pytest_runtest_protocol
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_callers.py", line 77 in _multicall
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_manager.py", line 115 in _hookexec
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_hooks.py", line 493 in __call__
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/main.py", line 350 in pytest_runtestloop
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_callers.py", line 77 in _multicall
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_manager.py", line 115 in _hookexec
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_hooks.py", line 493 in __call__
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/main.py", line 325 in _main
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/main.py", line 271 in wrap_session
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/main.py", line 318 in pytest_cmdline_main
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_callers.py", line 77 in _multicall
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_manager.py", line 115 in _hookexec
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/pluggy/_hooks.py", line 493 in __call__
File "/home/rui/anaconda3/envs/test-fold1218/lib/python3.10/site-packages/_pytest/config/__init__.py", line 169 in main
File "/home/rui/.pycharm_helpers/pycharm/_jb_pytest_runner.py", line 60 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, torch._C, torch._C._fft, torch._C._linalg, torch._C._nested, torch._C._nn, torch._C._sparse, torch._C._special, psutil._psutil_linux, psutil._psutil_posix, lmdb.cpython, Bio.PDB.ccealign, Bio.SeqIO._twoBitIO, yaml._yaml, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.ccalendar, 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.arrays, pandas._libs.tslib, pandas._libs.sparse, pandas._libs.indexing, pandas._libs.index, pandas._libs.internals, pandas._libs.join, pandas._libs.writers, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.groupby, pandas._libs.json, pandas._libs.parsers, pandas._libs.testing, PIL._imagingft, charset_normalizer.md, matplotlib._image, google._upb._message, scipy._lib._ccallback_c, scipy.sparse._sparsetools, _csparsetools, scipy.sparse._csparsetools, scipy.sparse.linalg._isolve._iterative, 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.linalg._flinalg, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, 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.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.__nnls, 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._statlib, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._mvn, scipy.stats._rcont.rcont (total: 174)
Process finished with exit code 134 (interrupted by signal 6:SIGABRT)
My environment is just pip install torch==2.0.1 with cuda 11.7. The testing sample is the basic one with query shape [256, 4, 256, 16].
In the past, I have already encountered this error which I could circumvent if I adjust the way the grid is defined--if I make the grid 1D, it works just fine, but not grid 2D. However, this is getting complicated with attention and stuff and I was wondering what could be the correct fix?
Hi,
I was trying to test
https://github.com/NVIDIA/apex/tree/master/apex/contrib/openfold_triton
with triton but encountered this error and cannot find the solution anywhere. It'd be great if I could get some pointers to check which part I did wrong.My environment is just
pip install torch==2.0.1
with cuda 11.7. The testing sample is the basic one with query shape[256, 4, 256, 16]
.In the past, I have already encountered this error which I could circumvent if I adjust the way the grid is defined--if I make the grid 1D, it works just fine, but not grid 2D. However, this is getting complicated with attention and stuff and I was wondering what could be the correct fix?
Best.