datong-new / point-gnn.pytorch Goto Github PK

Hi, thank you for your implementation of pytorch version for the paper.

Strangely, I meet the following problem when running train.sh

***** Error in `python3': free(): invalid pointer: 0x000055e59b686ba8 ***
======= Backtrace: =========
/lib/x86_64-linux-gnu/libc.so.6(+0x777f5)[0x7f88df7dc7f5]
/lib/x86_64-linux-gnu/libc.so.6(+0x8038a)[0x7f88df7e538a]
/lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7f88df7e958c]
/home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so(+0x13a842)[0x7f887fa88842]
/home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so(+0x13dff4)[0x7f887fa8bff4]
/home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so(+0x13e38b)[0x7f887fa8c38b]
/home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so(+0x1a6414)[0x7f887faf4414]
/home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so(+0x16f906)[0x7f887fabd906]
/home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so(PyInit_open3d+0xb7)[0x7f887fabf7f7]
python3(_PyImport_LoadDynamicModuleWithSpec+0x185)[0x55e598a50675]
python3(+0x23187e)[0x55e598a5087e]
python3(_PyMethodDef_RawFastCallDict+0x2d2)[0x55e598959c52]
python3(_PyCFunction_FastCallDict+0x21)[0x55e598959d31]
python3(_PyEval_EvalFrameDefault+0x5c6c)[0x55e5989f3ffc]
python3(_PyEval_EvalCodeWithName+0x2f9)[0x55e598934059]
python3(_PyFunction_FastCallKeywords+0x387)[0x55e598996307]
python3(_PyEval_EvalFrameDefault+0x4ade)[0x55e5989f2e6e]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x520)[0x55e5989ee8b0]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x6d6)[0x55e5989eea66]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x6d6)[0x55e5989eea66]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x6d6)[0x55e5989eea66]
python3(_PyFunction_FastCallDict+0x10b)[0x55e59893506b]
python3(+0x12ccfe)[0x55e59894bcfe]
python3(_PyObject_CallMethodIdObjArgs+0xbd)[0x55e5989ae74d]
python3(PyImport_ImportModuleLevelObject+0x1fe)[0x55e5989365de]
python3(_PyEval_EvalFrameDefault+0x296f)[0x55e5989f0cff]
python3(_PyEval_EvalCodeWithName+0x2f9)[0x55e598934059]
python3(PyEval_EvalCodeEx+0x44)[0x55e598934f24]
python3(PyEval_EvalCode+0x1c)[0x55e598934f4c]
python3(+0x1dee71)[0x55e5989fde71]
python3(_PyMethodDef_RawFastCallDict+0x2d2)[0x55e598959c52]
python3(_PyCFunction_FastCallDict+0x21)[0x55e598959d31]
python3(_PyEval_EvalFrameDefault+0x5c6c)[0x55e5989f3ffc]
python3(_PyEval_EvalCodeWithName+0x2f9)[0x55e598934059]
python3(_PyFunction_FastCallKeywords+0x387)[0x55e598996307]
python3(_PyEval_EvalFrameDefault+0x4ade)[0x55e5989f2e6e]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x520)[0x55e5989ee8b0]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x6d6)[0x55e5989eea66]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x6d6)[0x55e5989eea66]
python3(_PyFunction_FastCallDict+0x10b)[0x55e59893506b]
python3(+0x12ccfe)[0x55e59894bcfe]
python3(_PyObject_CallMethodIdObjArgs+0xbd)[0x55e5989ae74d]
python3(PyImport_ImportModuleLevelObject+0x1fe)[0x55e5989365de]
python3(_PyEval_EvalFrameDefault+0x296f)[0x55e5989f0cff]
python3(_PyEval_EvalCodeWithName+0x2f9)[0x55e598934059]
python3(PyEval_EvalCodeEx+0x44)[0x55e598934f24]
python3(PyEval_EvalCode+0x1c)[0x55e598934f4c]
python3(+0x1dee71)[0x55e5989fde71]
python3(_PyMethodDef_RawFastCallDict+0x2d2)[0x55e598959c52]
python3(_PyCFunction_FastCallDict+0x21)[0x55e598959d31]
python3(_PyEval_EvalFrameDefault+0x5c6c)[0x55e5989f3ffc]
python3(_PyEval_EvalCodeWithName+0x2f9)[0x55e598934059]
python3(_PyFunction_FastCallKeywords+0x387)[0x55e598996307]
python3(_PyEval_EvalFrameDefault+0x4ade)[0x55e5989f2e6e]
python3(_PyFunction_FastCallKeywords+0xfb)[0x55e59899607b]
python3(_PyEval_EvalFrameDefault+0x520)[0x55e5989ee8b0]
======= Memory map: ========
55e59881f000-55e59887a000 r--p 00000000 08:14 19139933 /home/cug/miniconda3/envs/pytorch_2/bin/python3.7
55e59887a000-55e598a5a000 r-xp 0005b000 08:14 19139933 /home/cug/miniconda3/envs/pytorch_2/bin/python3.7
55e598a5a000-55e598b00000 r--p 0023b000 08:14 19139933 /home/cug/miniconda3/envs/pytorch_2/bin/python3.7
55e598b01000-55e598b04000 r--p 002e1000 08:14 19139933 /home/cug/miniconda3/envs/pytorch_2/bin/python3.7
55e598b04000-55e598b6d000 rw-p 002e4000 08:14 19139933 /home/cug/miniconda3/envs/pytorch_2/bin/python3.7
55e598b6d000-55e598b8d000 rw-p 00000000 00:00 0
55e599e32000-55e59b69d000 rw-p 00000000 00:00 0 [heap]
7f8878000000-7f8878021000 rw-p 00000000 00:00 0
7f8878021000-7f887c000000 ---p 00000000 00:00 0
7f887e60c000-7f887e611000 r-xp 00000000 08:14 11804380 /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7f887e611000-7f887e810000 ---p 00005000 08:14 11804380 /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7f887e810000-7f887e811000 r--p 00004000 08:14 11804380 /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7f887e811000-7f887e812000 rw-p 00005000 08:14 11804380 /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7f887e812000-7f887e814000 r-xp 00000000 08:14 11804369 /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7f887e814000-7f887ea14000 ---p 00002000 08:14 11804369 /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7f887ea14000-7f887ea15000 r--p 00002000 08:14 11804369 /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7f887ea15000-7f887ea16000 rw-p 00003000 08:14 11804369 /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7f887ea16000-7f887ea27000 r-xp 00000000 08:14 11804382 /usr/lib/x86_64-linux-gnu/libXext.so.6.4.0
7f887ea27000-7f887ec26000 ---p 00011000 08:14 11804382 /usr/lib/x86_64-linux-gnu/libXext.so.6.4.0
7f887ec26000-7f887ec27000 r--p 00010000 08:14 11804382 /usr/lib/x86_64-linux-gnu/libXext.so.6.4.0
7f887ec27000-7f887ec28000 rw-p 00011000 08:14 11804382 /usr/lib/x86_64-linux-gnu/libXext.so.6.4.0
7f887ec28000-7f887ec49000 r-xp 00000000 08:14 11805749 /usr/lib/x86_64-linux-gnu/libxcb.so.1.1.0
7f887ec49000-7f887ee48000 ---p 00021000 08:14 11805749 /usr/lib/x86_64-linux-gnu/libxcb.so.1.1.0
7f887ee48000-7f887ee49000 r--p 00020000 08:14 11805749 /usr/lib/x86_64-linux-gnu/libxcb.so.1.1.0
7f887ee49000-7f887ee4a000 rw-p 00021000 08:14 11805749 /usr/lib/x86_64-linux-gnu/libxcb.so.1.1.0
7f887ee4a000-7f887eed4000 r-xp 00000000 08:14 11932788 /usr/lib/nvidia-430/libGLdispatch.so.0
7f887eed4000-7f887f0d4000 ---p 0008a000 08:14 11932788 /usr/lib/nvidia-430/libGLdispatch.so.0
7f887f0d4000-7f887f0fd000 rw-p 0008a000 08:14 11932788 /usr/lib/nvidia-430/libGLdispatch.so.0
7f887f0fd000-7f887f11d000 rw-p 00000000 00:00 0
7f887f11d000-7f887f12d000 r-xp 00000000 08:14 11932784 /usr/lib/nvidia-430/libGLX.so.0
7f887f12d000-7f887f32c000 ---p 00010000 08:14 11932784 /usr/lib/nvidia-430/libGLX.so.0
7f887f32c000-7f887f32d000 rw-p 0000f000 08:14 11932784 /usr/lib/nvidia-430/libGLX.so.0
7f887f32d000-7f887f34d000 rw-p 00000000 00:00 0
7f887f34d000-7f887f482000 r-xp 00000000 08:14 11807373 /usr/lib/x86_64-linux-gnu/libX11.so.6.3.0
7f887f482000-7f887f682000 ---p 00135000 08:14 11807373 /usr/lib/x86_64-linux-gnu/libX11.so.6.3.0
7f887f682000-7f887f683000 r--p 00135000 08:14 11807373 /usr/lib/x86_64-linux-gnu/libX11.so.6.3.0
7f887f683000-7f887f687000 rw-p 00136000 08:14 11807373 /usr/lib/x86_64-linux-gnu/libX11.so.6.3.0
7f887f687000-7f887f715000 r-xp 00000000 08:14 11932758 /usr/lib/nvidia-430/libGL.so.1.7.0
7f887f715000-7f887f914000 ---p 0008e000 08:14 11932758 /usr/lib/nvidia-430/libGL.so.1.7.0
7f887f914000-7f887f92f000 rw-p 0008d000 08:14 11932758 /usr/lib/nvidia-430/libGL.so.1.7.0
7f887f92f000-7f887f930000 rw-p 00000000 00:00 0
7f887f94e000-7f887ff24000 r-xp 00000000 08:14 19923504 /home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so
7f887ff24000-7f8880123000 ---p 005d6000 08:14 19923504 /home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so
7f8880123000-7f888013c000 r--p 005d5000 08:14 19923504 /home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so
7f888013c000-7f8880143000 rw-p 005ee000 08:14 19923504 /home/cug/.local/lib/python3.7/site-packages/open3d/open3d.cpython-37m-x86_64-linux-gnu.so
7f8880143000-7f8880174000 rw-p 00000000 00:00 0
7f8880174000-7f8880176000 r--p 00000000 08:14 19138879 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_json.cpython-37m-x86_64-linux-gnu.so
7f8880176000-7f8880184000 r-xp 00002000 08:14 19138879 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_json.cpython-37m-x86_64-linux-gnu.so
7f8880184000-7f8880186000 r--p 00010000 08:14 19138879 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_json.cpython-37m-x86_64-linux-gnu.so
7f8880186000-7f8880187000 r--p 00011000 08:14 19138879 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_json.cpython-37m-x86_64-linux-gnu.so
7f8880187000-7f8880188000 rw-p 00012000 08:14 19138879 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_json.cpython-37m-x86_64-linux-gnu.so
7f8880188000-7f88802c8000 rw-p 00000000 00:00 0
7f88802c8000-7f88802cb000 r--p 00000000 08:14 19138902 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/unicodedata.cpython-37m-x86_64-linux-gnu.so
7f88802cb000-7f88802d1000 r-xp 00003000 08:14 19138902 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/unicodedata.cpython-37m-x86_64-linux-gnu.so
7f88802d1000-7f88803b2000 r--p 00009000 08:14 19138902 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/unicodedata.cpython-37m-x86_64-linux-gnu.so
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7f88803b3000-7f88803d0000 rw-p 000ea000 08:14 19138902 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/unicodedata.cpython-37m-x86_64-linux-gnu.so
7f88803d0000-7f8880450000 rw-p 00000000 00:00 0
7f8880450000-7f888046c000 r--p 00000000 08:14 12059575 /home/cug/miniconda3/envs/pytorch_2/lib/libssl.so.1.0.0
7f888046c000-7f88804ad000 r-xp 0001c000 08:14 12059575 /home/cug/miniconda3/envs/pytorch_2/lib/libssl.so.1.0.0
7f88804ad000-7f88804be000 r--p 0005d000 08:14 12059575 /home/cug/miniconda3/envs/pytorch_2/lib/libssl.so.1.0.0
7f88804be000-7f88804c3000 r--p 0006d000 08:14 12059575 /home/cug/miniconda3/envs/pytorch_2/lib/libssl.so.1.0.0
7f88804c3000-7f88804c9000 rw-p 00072000 08:14 12059575 /home/cug/miniconda3/envs/pytorch_2/lib/libssl.so.1.0.0
7f88804c9000-7f88804d3000 r--p 00000000 08:14 19138895 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_ssl.cpython-37m-x86_64-linux-gnu.so
7f88804d3000-7f88804de000 r-xp 0000a000 08:14 19138895 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_ssl.cpython-37m-x86_64-linux-gnu.so
7f88804de000-7f88804e4000 r--p 00015000 08:14 19138895 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_ssl.cpython-37m-x86_64-linux-gnu.so
7f88804e4000-7f88804e5000 ---p 0001b000 08:14 19138895 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_ssl.cpython-37m-x86_64-linux-gnu.so
7f88804e5000-7f88804e6000 r--p 0001b000 08:14 19138895 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_ssl.cpython-37m-x86_64-linux-gnu.so
7f88804e6000-7f88804eb000 rw-p 0001c000 08:14 19138895 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_ssl.cpython-37m-x86_64-linux-gnu.so
7f88804eb000-7f88805eb000 rw-p 00000000 00:00 0
7f88805eb000-7f88805ed000 r--p 00000000 08:14 19138848 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_multiprocessing.cpython-37m-x86_64-linux-gnu.so
7f88805ed000-7f88805ee000 r-xp 00002000 08:14 19138848 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_multiprocessing.cpython-37m-x86_64-linux-gnu.so
7f88805ee000-7f88805ef000 r--p 00003000 08:14 19138848 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_multiprocessing.cpython-37m-x86_64-linux-gnu.so
7f88805ef000-7f88805f0000 r--p 00003000 08:14 19138848 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_multiprocessing.cpython-37m-x86_64-linux-gnu.so
7f88805f0000-7f88805f1000 rw-p 00004000 08:14 19138848 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_multiprocessing.cpython-37m-x86_64-linux-gnu.so
7f88805f1000-7f88808f1000 rw-p 00000000 00:00 0
7f88808f1000-7f88808f5000 r--p 00000000 08:14 19138880 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/array.cpython-37m-x86_64-linux-gnu.so
7f88808f5000-7f88808fc000 r-xp 00004000 08:14 19138880 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/array.cpython-37m-x86_64-linux-gnu.so
7f88808fc000-7f88808ff000 r--p 0000b000 08:14 19138880 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/array.cpython-37m-x86_64-linux-gnu.so
7f88808ff000-7f8880900000 ---p 0000e000 08:14 19138880 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/array.cpython-37m-x86_64-linux-gnu.so
7f8880900000-7f8880901000 r--p 0000e000 08:14 19138880 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/array.cpython-37m-x86_64-linux-gnu.so
7f8880901000-7f8880904000 rw-p 0000f000 08:14 19138880 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/array.cpython-37m-x86_64-linux-gnu.so
7f8880904000-7f8880909000 r--p 00000000 08:14 19138889 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_socket.cpython-37m-x86_64-linux-gnu.so
7f8880909000-7f8880917000 r-xp 00005000 08:14 19138889 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_socket.cpython-37m-x86_64-linux-gnu.so
7f8880917000-7f888091c000 r--p 00013000 08:14 19138889 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_socket.cpython-37m-x86_64-linux-gnu.so
7f888091c000-7f888091d000 r--p 00017000 08:14 19138889 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_socket.cpython-37m-x86_64-linux-gnu.so
7f888091d000-7f8880922000 rw-p 00018000 08:14 19138889 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_socket.cpython-37m-x86_64-linux-gnu.so
7f8880922000-7f88811b9000 rw-p 00000000 00:00 0
7f88811b9000-7f8882de0000 r-xp 00000000 08:14 19272032 /home/cug/miniconda3/envs/pytorch_2/lib/libcublasLt.so.10.2.1.243
7f8882de0000-7f8882fdf000 ---p 01c27000 08:14 19272032 /home/cug/miniconda3/envs/pytorch_2/lib/libcublasLt.so.10.2.1.243
7f8882fdf000-7f8883054000 rw-p 01c26000 08:14 19272032 /home/cug/miniconda3/envs/pytorch_2/lib/libcublasLt.so.10.2.1.243
7f8883054000-7f888305d000 rw-p 00000000 00:00 0
7f888305d000-7f888305f000 rw-p 01c9c000 08:14 19272032 /home/cug/miniconda3/envs/pytorch_2/lib/libcublasLt.so.10.2.1.243
7f888305f000-7f888a0d0000 r-xp 00000000 08:14 19272036 /home/cug/miniconda3/envs/pytorch_2/lib/libcusparse.so.10.3.0.243
7f888a0d0000-7f888a2d0000 ---p 07071000 08:14 19272036 /home/cug/miniconda3/envs/pytorch_2/lib/libcusparse.so.10.3.0.243
7f888a2d0000-7f888a2df000 rw-p 07071000 08:14 19272036 /home/cug/miniconda3/envs/pytorch_2/lib/libcusparse.so.10.3.0.243
7f888a2df000-7f888a2e6000 rw-p 00000000 00:00 0
7f888a2e6000-7f888a2ea000 rw-p 07080000 08:14 19272036 /home/cug/miniconda3/envs/pytorch_2/lib/libcusparse.so.10.3.0.243
7f888a2ea000-7f888a2f4000 r--p 00000000 08:14 15075559 /home/cug/miniconda3/envs/pytorch_2/lib/libgomp.so.1.0.0
7f888a2f4000-7f888a30b000 r-xp 0000a000 08:14 15075559 /home/cug/miniconda3/envs/pytorch_2/lib/libgomp.so.1.0.0
7f888a30b000-7f888a314000 r--p 00021000 08:14 15075559 /home/cug/miniconda3/envs/pytorch_2/lib/libgomp.so.1.0.0
7f888a314000-7f888a315000 ---p 0002a000 08:14 15075559 /home/cug/miniconda3/envs/pytorch_2/lib/libgomp.so.1.0.0
7f888a315000-7f888a316000 r--p 0002a000 08:14 15075559 /home/cug/miniconda3/envs/pytorch_2/lib/libgomp.so.1.0.0
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7f88dcfa2000-7f88dcfa4000 r--p 00000000 08:14 19138851 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_random.cpython-37m-x86_64-linux-gnu.so
7f88dcfa4000-7f88dcfa6000 r-xp 00002000 08:14 19138851 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_random.cpython-37m-x86_64-linux-gnu.so
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7f88dcfa7000-7f88dcfa8000 r--p 00004000 08:14 19138851 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_random.cpython-37m-x86_64-linux-gnu.so
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7f88dcfa9000-7f88dcfaa000 r--p 00000000 08:14 19138842 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_bisect.cpython-37m-x86_64-linux-gnu.so
7f88dcfaa000-7f88dcfab000 r-xp 00001000 08:14 19138842 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_bisect.cpython-37m-x86_64-linux-gnu.so
7f88dcfab000-7f88dcfac000 r--p 00002000 08:14 19138842 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_bisect.cpython-37m-x86_64-linux-gnu.so
7f88dcfac000-7f88dcfad000 r--p 00002000 08:14 19138842 /home/cug/miniconda3/envs/pytorch_2/lib/python3.7/lib-dynload/_bisect.cpython-37m-x86_64-linux-gnu.sotrain.sh: 行 2: 159180 已放弃 python3 mytrain.py configs/car_auto_T3_train_train_config configs/car_auto_T3_train_config --dataset_root_dir data**

Do you know why and how to solve it ?
or can you tell me the package version in the enviroment of your experiment?

thank you very much!

In model.py, there are some bugs in class GraphNetAutoCenter.

def forward(self, input_vertex_features,
        input_vertex_coordinates,
        keypoint_indices,
        edges):
        
        s_vertex_features = input_vertex_features[edges[:, 0]]
        s_vertex_coordinates = input_vertex_coordinates[edges[:, 1]] # Should it be edges[:, 0] here?

        if self.auto_offset:
            offset = self.auto_offset_fn(input_vertex_features)
            input_vertex_coordinates = input_vertex_coordinates + offset

       
        d_vertex_coordinates = input_vertex_coordinates[edges[:, 1]]

        # Prepare initial edge features
        edge_features = torch.cat([s_vertex_features, s_vertex_coordinates - s_vertex_coordinates], dim=-1) # The second input of torch.cat is a zero tensor.
        
        # Extract edge features
        edge_features = self.edge_feature_fn(edge_features)

        # Aggregate edge features
        aggregated_edge_features = max_aggregation_fn(edge_features, edges[:,1], len(keypoint_indices))

        # Update vertex features
        update_features = self.update_fn(aggregated_edge_features)
        output_vertex_features  = update_features + input_vertex_features
        return output_vertex_features 

It takes me about 12mins to train the Car model for each epoch with GTX 1070 (8G) using the TF version(https://github.com/WeijingShi/Point-GNN), but it takes me about 20mins to train the model with your PyTorch version. I find there may be some advances in the max_aggregation_fn function in the file model.py.

In this way, I can train the model in about 12mins each epoch with my computer.

When I try to run training
bash train.sh
train.sh: line 2: 48996 Segmentation fault (core dumped) python3 mytrain.py configs/car_auto_T3_train_train_config configs/car_auto_T3_train_config --dataset_root_dir data

Can I just use Pytorch?

@ShuDeng hi thanks for sharing the code base i have few queries

1. can you we run the inference on the cpu
2. can you please share the trained model
3. did u evaluate the trained model if so can you share the code base and the metrics
   THanks in advance

Thank you very much for your work, it is very useful for my study！
Do I only need to run
python3 mytrain.py configs/car_auto_T3_train_train_config configs/car_auto_T3_train_config --dataset_root_dir data
for training?

What is the difference between encoded_boxes and valid_boxes obtained in a batch?

I think there is a mistake in the model.py: 117, where
point_set_keypoint_coordinates = point_features[point_set_keypoint_indices[:, 0]]
should be:
point_set_keypoint_coordinates = point_coordinates[point_set_keypoint_indices[:, 0]]
@ShuDeng

@ShuDeng @Wu-Shudeng in the training pipeline of mytrain.py in line batch = data_provider.provide_batch([1545, 1546]) y is it specified 1545,1546 can you clarify on this , if i am training the model i am getting error

How can we evaluate this model and visualize results (same function as run.py) ?

Thanks