Closed wzw773828204 closed 1 year ago
Mylszd
commented
1 year ago +1 docker镜像nvcr.io/nvidia/pytorch:22.08-py3 torch cu11.7 ubuntu20.04 显卡1080ti
测试python实例，选择0号GPU出现如下错误 Processing batch 1 of 1 Line 679: '' failed: no kernel image is available for execution on the device
选择1号GPU 导致机器宕机重启
milesp-nvidia
commented
1 year ago Hi @Mylszd and @wzw773828204, if you can run the print_env.sh script in the root directory of the repo and post the results here, that will be very helpful.
zhaozhiming37
commented
1 year ago @milesp-nvidia I have the same issue, and my env:
**git***
./print_env.sh: 24: [: true: unexpected operator
Not inside a git repository
***OS Information***
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=20.04
DISTRIB_CODENAME=focal
DISTRIB_DESCRIPTION="Ubuntu 20.04.1 LTS"
NAME="Ubuntu"
VERSION="20.04.1 LTS (Focal Fossa)"
ID=ubuntu
ID_LIKE=debian
PRETTY_NAME="Ubuntu 20.04.1 LTS"
VERSION_ID="20.04"
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
VERSION_CODENAME=focal
UBUNTU_CODENAME=focal
Linux ubuntu20-04 5.15.0-56-generic #62~20.04.1-Ubuntu SMP Tue Nov 22 21:24:20 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux
***GPU Information***
Thu Jan 5 11:41:31 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.76 Driver Version: 515.76 CUDA Version: 11.7 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA P102-100 Off | 00000000:01:00.0 Off | N/A |
| 38% 41C P0 74W / 250W | 3126MiB / 10240MiB | 46% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1008 G /usr/lib/xorg/Xorg 70MiB |
| 0 N/A N/A 2000 G /usr/lib/xorg/Xorg 487MiB |
| 0 N/A N/A 2195 G /usr/bin/gnome-shell 56MiB |
| 0 N/A N/A 3120 G ...nlogin/bin/sunloginclient 13MiB |
| 0 N/A N/A 3707 G ...2gtk-4.0/WebKitWebProcess 10MiB |
| 0 N/A N/A 4473 G ...RendererForSitePerProcess 76MiB |
| 0 N/A N/A 457832 G ...veSuggestionsOnlyOnDemand 54MiB |
| 0 N/A N/A 803021 C tritonserver 2006MiB |
| 0 N/A N/A 1806407 C /usr/bin/python3.8 125MiB |
| 0 N/A N/A 1873640 C /usr/bin/python3.8 125MiB |
| 0 N/A N/A 1985449 G ...961838332868937147,131072 79MiB |
+-----------------------------------------------------------------------------+
***CPU***
架构： x86_64
CPU 运行模式： 32-bit, 64-bit
字节序： Little Endian
Address sizes: 39 bits physical, 48 bits virtual
CPU: 12
在线 CPU 列表： 0-11
每个核的线程数： 2
每个座的核数： 6
座： 1
NUMA 节点： 1
厂商 ID： GenuineIntel
CPU 系列： 6
型号： 158
型号名称： Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
步进： 10
CPU MHz： 3506.627
CPU 最大 MHz： 4600.0000
CPU 最小 MHz： 800.0000
BogoMIPS： 6399.96
L1d 缓存： 192 KiB
L1i 缓存： 192 KiB
L2 缓存： 1.5 MiB
L3 缓存： 12 MiB
NUMA 节点0 CPU： 0-11
Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported
Vulnerability L1tf: Mitigation; PTE Inversion
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed: Mitigation; IBRS
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Mitigation; Microcode
Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT vulnerable
标记： fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc aarch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp md_clear flush_l1d
***CMake***
/usr/local/bin/cmake
cmake version 3.22.6
CMake suite maintained and supported by Kitware (kitware.com/cmake).
***g++***
/usr/bin/g++
g++ (Ubuntu 11.1.0-1ubuntu1~20.04) 11.1.0
Copyright (C) 2021 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
***nvcc***
/usr/local/cuda/bin/nvcc
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Jun__8_16:49:14_PDT_2022
Cuda compilation tools, release 11.7, V11.7.99
Build cuda_11.7.r11.7/compiler.31442593_0
***Python***
/home/zzm/software/anaconda3/bin/python
Python 3.9.13
***Environment Variables***
PATH : /usr/local/cuda/bin:/home/zzm/software/anaconda3/bin:/home/zzm/software/anaconda3/bin:/home/zzm/software/anaconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
LD_LIBRARY_PATH : /usr/local/cuda/lib64
NUMBAPRO_NVVM :
NUMBAPRO_LIBDEVICE :
CONDA_PREFIX : /home/zzm/software/anaconda3
PYTHON_PATH :
***conda packages***
conda is /home/zzm/software/anaconda3/bin/conda
/home/zzm/software/anaconda3/bin/conda
# packages in environment at /home/zzm/software/anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py39h06a4308_1
_libgcc_mutex 0.1 main
_openmp_mutex 5.1 1_gnu
alabaster 0.7.12 pyhd3eb1b0_0
anaconda 2022.10 py39_0
anaconda-client 1.11.0 py39h06a4308_0
anaconda-navigator 2.3.1 py39h06a4308_0
anaconda-project 0.11.1 py39h06a4308_0
anyio 3.5.0 py39h06a4308_0
appdirs 1.4.4 pyhd3eb1b0_0
argon2-cffi 21.3.0 pyhd3eb1b0_0
argon2-cffi-bindings 21.2.0 py39h7f8727e_0
arrow 1.2.2 pyhd3eb1b0_0
astroid 2.11.7 py39h06a4308_0
astropy 5.1 py39h7deecbd_0
atomicwrites 1.4.0 py_0
attrs 21.4.0 pyhd3eb1b0_0
automat 20.2.0 py_0
autopep8 1.6.0 pyhd3eb1b0_1
babel 2.9.1 pyhd3eb1b0_0
backcall 0.2.0 pyhd3eb1b0_0
backports 1.1 pyhd3eb1b0_0
backports.functools_lru_cache 1.6.4 pyhd3eb1b0_0
backports.tempfile 1.0 pyhd3eb1b0_1
backports.weakref 1.0.post1 py_1
bcrypt 3.2.0 py39h5eee18b_1
beautifulsoup4 4.11.1 py39h06a4308_0
binaryornot 0.4.4 pyhd3eb1b0_1
bitarray 2.5.1 py39h5eee18b_0
bkcharts 0.2 py39h06a4308_1
black 22.6.0 py39h06a4308_0
blas 1.0 mkl
bleach 4.1.0 pyhd3eb1b0_0
blosc 1.21.0 h4ff587b_1
bokeh 2.4.3 py39h06a4308_0
boto3 1.24.28 py39h06a4308_0
botocore 1.27.28 py39h06a4308_0
bottleneck 1.3.5 py39h7deecbd_0
brotli 1.0.9 h5eee18b_7
brotli-bin 1.0.9 h5eee18b_7
brotlipy 0.7.0 py39h27cfd23_1003
brunsli 0.1 h2531618_0
bzip2 1.0.8 h7b6447c_0
c-ares 1.18.1 h7f8727e_0
ca-certificates 2022.07.19 h06a4308_0
certifi 2022.9.14 py39h06a4308_0
cffi 1.15.1 py39h74dc2b5_0
cfitsio 3.470 h5893167_7
chardet 4.0.0 py39h06a4308_1003
charls 2.2.0 h2531618_0
charset-normalizer 2.0.4 pyhd3eb1b0_0
click 8.0.4 py39h06a4308_0
cloudpickle 2.0.0 pyhd3eb1b0_0
clyent 1.2.2 py39h06a4308_1
colorama 0.4.5 py39h06a4308_0
colorcet 3.0.0 py39h06a4308_0
conda 22.9.0 py39h06a4308_0
conda-build 3.22.0 py39h06a4308_0
conda-content-trust 0.1.3 py39h06a4308_0
conda-env 2.6.0 1
conda-pack 0.6.0 pyhd3eb1b0_0
conda-package-handling 1.9.0 py39h5eee18b_0
conda-repo-cli 1.0.20 py39h06a4308_0
conda-token 0.4.0 pyhd3eb1b0_0
conda-verify 3.4.2 py_1
constantly 15.1.0 pyh2b92418_0
cookiecutter 1.7.3 pyhd3eb1b0_0
cryptography 37.0.1 py39h9ce1e76_0
cssselect 1.1.0 pyhd3eb1b0_0
curl 7.84.0 h5eee18b_0
cycler 0.11.0 pyhd3eb1b0_0
cython 0.29.32 py39h6a678d5_0
cytoolz 0.11.0 py39h27cfd23_0
daal4py 2021.6.0 py39h79cecc1_1
dal 2021.6.0 hdb19cb5_916
dask 2022.7.0 py39h06a4308_0
dask-core 2022.7.0 py39h06a4308_0
dataclasses 0.8 pyh6d0b6a4_7
datashader 0.14.1 py39h06a4308_0
datashape 0.5.4 py39h06a4308_1
dbus 1.13.18 hb2f20db_0
debugpy 1.5.1 py39h295c915_0
decorator 5.1.1 pyhd3eb1b0_0
defusedxml 0.7.1 pyhd3eb1b0_0
diff-match-patch 20200713 pyhd3eb1b0_0
dill 0.3.4 pyhd3eb1b0_0
distributed 2022.7.0 py39h06a4308_0
docutils 0.18.1 py39h06a4308_3
entrypoints 0.4 py39h06a4308_0
et_xmlfile 1.1.0 py39h06a4308_0
expat 2.4.9 h6a678d5_0
fftw 3.3.9 h27cfd23_1
filelock 3.6.0 pyhd3eb1b0_0
flake8 4.0.1 pyhd3eb1b0_1
flask 1.1.2 pyhd3eb1b0_0
fontconfig 2.13.1 h6c09931_0
fonttools 4.25.0 pyhd3eb1b0_0
freetype 2.11.0 h70c0345_0
fsspec 2022.7.1 py39h06a4308_0
future 0.18.2 py39h06a4308_1
gensim 4.1.2 py39h295c915_0
giflib 5.2.1 h7b6447c_0
glib 2.69.1 h4ff587b_1
glob2 0.7 pyhd3eb1b0_0
gmp 6.2.1 h295c915_3
gmpy2 2.1.2 py39heeb90bb_0
greenlet 1.1.1 py39h295c915_0
gst-plugins-base 1.14.0 h8213a91_2
gstreamer 1.14.0 h28cd5cc_2
h5py 3.7.0 py39h737f45e_0
hdf5 1.10.6 h3ffc7dd_1
heapdict 1.0.1 pyhd3eb1b0_0
holoviews 1.15.0 py39h06a4308_0
hvplot 0.8.0 py39h06a4308_0
hyperlink 21.0.0 pyhd3eb1b0_0
icu 58.2 he6710b0_3
idna 3.3 pyhd3eb1b0_0
imagecodecs 2021.8.26 py39hf0132c2_1
imageio 2.19.3 py39h06a4308_0
imagesize 1.4.1 py39h06a4308_0
importlib-metadata 4.11.3 py39h06a4308_0
importlib_metadata 4.11.3 hd3eb1b0_0
incremental 21.3.0 pyhd3eb1b0_0
inflection 0.5.1 py39h06a4308_0
iniconfig 1.1.1 pyhd3eb1b0_0
intake 0.6.5 pyhd3eb1b0_0
intel-openmp 2021.4.0 h06a4308_3561
intervaltree 3.1.0 pyhd3eb1b0_0
ipykernel 6.15.2 py39h06a4308_0
ipython 7.31.1 py39h06a4308_1
ipython_genutils 0.2.0 pyhd3eb1b0_1
ipywidgets 7.6.5 pyhd3eb1b0_1
isort 5.9.3 pyhd3eb1b0_0
itemadapter 0.3.0 pyhd3eb1b0_0
itemloaders 1.0.4 pyhd3eb1b0_1
itsdangerous 2.0.1 pyhd3eb1b0_0
jdcal 1.4.1 pyhd3eb1b0_0
jedi 0.18.1 py39h06a4308_1
jeepney 0.7.1 pyhd3eb1b0_0
jellyfish 0.9.0 py39h7f8727e_0
jinja2 2.11.3 pyhd3eb1b0_0
jinja2-time 0.2.0 pyhd3eb1b0_3
jmespath 0.10.0 pyhd3eb1b0_0
joblib 1.1.0 pyhd3eb1b0_0
jpeg 9e h7f8727e_0
jq 1.6 h27cfd23_1000
json5 0.9.6 pyhd3eb1b0_0
jsonschema 4.16.0 py39h06a4308_0
jupyter 1.0.0 py39h06a4308_8
jupyter_client 7.3.4 py39h06a4308_0
jupyter_console 6.4.3 pyhd3eb1b0_0
jupyter_core 4.11.1 py39h06a4308_0
jupyter_server 1.18.1 py39h06a4308_0
jupyterlab 3.4.4 py39h06a4308_0
jupyterlab_pygments 0.1.2 py_0
jupyterlab_server 2.10.3 pyhd3eb1b0_1
jupyterlab_widgets 1.0.0 pyhd3eb1b0_1
jxrlib 1.1 h7b6447c_2
keyring 23.4.0 py39h06a4308_0
kiwisolver 1.4.2 py39h295c915_0
krb5 1.19.2 hac12032_0
lazy-object-proxy 1.6.0 py39h27cfd23_0
lcms2 2.12 h3be6417_0
ld_impl_linux-64 2.38 h1181459_1
lerc 3.0 h295c915_0
libaec 1.0.4 he6710b0_1
libarchive 3.6.1 hab531cd_0
libbrotlicommon 1.0.9 h5eee18b_7
libbrotlidec 1.0.9 h5eee18b_7
libbrotlienc 1.0.9 h5eee18b_7
libclang 10.0.1 default_hb85057a_2
libcurl 7.84.0 h91b91d3_0
libdeflate 1.8 h7f8727e_5
libedit 3.1.20210910 h7f8727e_0
libev 4.33 h7f8727e_1
libevent 2.1.12 h8f2d780_0
libffi 3.3 he6710b0_2
libgcc-ng 11.2.0 h1234567_1
libgfortran-ng 11.2.0 h00389a5_1
libgfortran5 11.2.0 h1234567_1
libgomp 11.2.0 h1234567_1
libidn2 2.3.2 h7f8727e_0
liblief 0.11.5 h295c915_1
libllvm10 10.0.1 hbcb73fb_5
libllvm11 11.1.0 h9e868ea_5
libnghttp2 1.46.0 hce63b2e_0
libpng 1.6.37 hbc83047_0
libpq 12.9 h16c4e8d_3
libsodium 1.0.18 h7b6447c_0
libspatialindex 1.9.3 h2531618_0
libssh2 1.10.0 h8f2d780_0
libstdcxx-ng 11.2.0 h1234567_1
libtiff 4.4.0 hecacb30_0
libunistring 0.9.10 h27cfd23_0
libuuid 1.0.3 h7f8727e_2
libwebp 1.2.2 h55f646e_0
libwebp-base 1.2.2 h7f8727e_0
libxcb 1.15 h7f8727e_0
libxkbcommon 1.0.1 hfa300c1_0
libxml2 2.9.14 h74e7548_0
libxslt 1.1.35 h4e12654_0
libzopfli 1.0.3 he6710b0_0
llvmlite 0.38.0 py39h4ff587b_0
locket 1.0.0 py39h06a4308_0
lxml 4.9.1 py39h1edc446_0
lz4 3.1.3 py39h27cfd23_0
lz4-c 1.9.3 h295c915_1
lzo 2.10 h7b6447c_2
markdown 3.3.4 py39h06a4308_0
markupsafe 2.0.1 py39h27cfd23_0
matplotlib 3.5.2 py39h06a4308_0
matplotlib-base 3.5.2 py39hf590b9c_0
matplotlib-inline 0.1.6 py39h06a4308_0
mccabe 0.7.0 pyhd3eb1b0_0
mistune 0.8.4 py39h27cfd23_1000
mkl 2021.4.0 h06a4308_640
mkl-service 2.4.0 py39h7f8727e_0
mkl_fft 1.3.1 py39hd3c417c_0
mkl_random 1.2.2 py39h51133e4_0
mock 4.0.3 pyhd3eb1b0_0
mpc 1.1.0 h10f8cd9_1
mpfr 4.0.2 hb69a4c5_1
mpi 1.0 mpich
mpich 3.3.2 external_0
mpmath 1.2.1 py39h06a4308_0
msgpack-python 1.0.3 py39hd09550d_0
multipledispatch 0.6.0 py39h06a4308_0
munkres 1.1.4 py_0
mypy_extensions 0.4.3 py39h06a4308_1
navigator-updater 0.3.0 py39h06a4308_0
nbclassic 0.3.5 pyhd3eb1b0_0
nbclient 0.5.13 py39h06a4308_0
nbconvert 6.4.4 py39h06a4308_0
nbformat 5.5.0 py39h06a4308_0
ncurses 6.3 h5eee18b_3
nest-asyncio 1.5.5 py39h06a4308_0
networkx 2.8.4 py39h06a4308_0
nltk 3.7 pyhd3eb1b0_0
nose 1.3.7 pyhd3eb1b0_1008
notebook 6.4.12 py39h06a4308_0
nspr 4.33 h295c915_0
nss 3.74 h0370c37_0
numba 0.55.1 py39h51133e4_0
numexpr 2.8.3 py39h807cd23_0
numpy 1.21.5 py39h6c91a56_3
numpy-base 1.21.5 py39ha15fc14_3
numpydoc 1.4.0 py39h06a4308_0
olefile 0.46 pyhd3eb1b0_0
oniguruma 6.9.7.1 h27cfd23_0
openjpeg 2.4.0 h3ad879b_0
openpyxl 3.0.10 py39h5eee18b_0
openssl 1.1.1q h7f8727e_0
packaging 21.3 pyhd3eb1b0_0
pandas 1.4.4 py39h6a678d5_0
pandocfilters 1.5.0 pyhd3eb1b0_0
panel 0.13.1 py39h06a4308_0
param 1.12.0 pyhd3eb1b0_0
parsel 1.6.0 py39h06a4308_0
parso 0.8.3 pyhd3eb1b0_0
partd 1.2.0 pyhd3eb1b0_1
patch 2.7.6 h7b6447c_1001
patchelf 0.13 h295c915_0
pathlib 1.0.1 pyhd3eb1b0_1
pathspec 0.9.0 py39h06a4308_0
patsy 0.5.2 py39h06a4308_1
pcre 8.45 h295c915_0
pep8 1.7.1 py39h06a4308_1
pexpect 4.8.0 pyhd3eb1b0_3
pickleshare 0.7.5 pyhd3eb1b0_1003
pillow 9.2.0 py39hace64e9_1
pip 22.3.1 pypi_0 pypi
pkginfo 1.8.2 pyhd3eb1b0_0
platformdirs 2.5.2 py39h06a4308_0
plotly 5.9.0 py39h06a4308_0
pluggy 1.0.0 py39h06a4308_1
ply 3.11 py39h06a4308_0
poyo 0.5.0 pyhd3eb1b0_0
prometheus_client 0.14.1 py39h06a4308_0
prompt-toolkit 3.0.20 pyhd3eb1b0_0
prompt_toolkit 3.0.20 hd3eb1b0_0
protego 0.1.16 py_0
psutil 5.9.0 py39h5eee18b_0
ptyprocess 0.7.0 pyhd3eb1b0_2
py 1.11.0 pyhd3eb1b0_0
py-lief 0.11.5 py39h295c915_1
pyasn1 0.4.8 pyhd3eb1b0_0
pyasn1-modules 0.2.8 py_0
pycodestyle 2.8.0 pyhd3eb1b0_0
pycosat 0.6.3 py39h27cfd23_0
pycparser 2.21 pyhd3eb1b0_0
pyct 0.4.8 py39h06a4308_1
pycurl 7.45.1 py39h8f2d780_0
pydispatcher 2.0.5 py39h06a4308_2
pydocstyle 6.1.1 pyhd3eb1b0_0
pyerfa 2.0.0 py39h27cfd23_0
pyflakes 2.4.0 pyhd3eb1b0_0
pygments 2.11.2 pyhd3eb1b0_0
pyhamcrest 2.0.2 pyhd3eb1b0_2
pyjwt 2.4.0 py39h06a4308_0
pylint 2.14.5 py39h06a4308_0
pyls-spyder 0.4.0 pyhd3eb1b0_0
pyodbc 4.0.34 py39h6a678d5_0
pyopenssl 22.0.0 pyhd3eb1b0_0
pyparsing 3.0.9 py39h06a4308_0
pyqt 5.15.7 py39h6a678d5_1
pyqt5-sip 12.11.0 py39h6a678d5_1
pyqtwebengine 5.15.7 py39h6a678d5_1
pyrsistent 0.18.0 py39heee7806_0
pysocks 1.7.1 py39h06a4308_0
pytables 3.6.1 py39h77479fe_1
pytest 7.1.2 py39h06a4308_0
python 3.9.13 haa1d7c7_1
python-dateutil 2.8.2 pyhd3eb1b0_0
python-fastjsonschema 2.16.2 py39h06a4308_0
python-libarchive-c 2.9 pyhd3eb1b0_1
python-lsp-black 1.2.1 py39h06a4308_0
python-lsp-jsonrpc 1.0.0 pyhd3eb1b0_0
python-lsp-server 1.5.0 py39h06a4308_0
python-slugify 5.0.2 pyhd3eb1b0_0
python-snappy 0.6.0 py39h2531618_3
pytz 2022.1 py39h06a4308_0
pyviz_comms 2.0.2 pyhd3eb1b0_0
pywavelets 1.3.0 py39h7f8727e_0
pyxdg 0.27 pyhd3eb1b0_0
pyyaml 6.0 py39h7f8727e_1
pyzmq 23.2.0 py39h6a678d5_0
qdarkstyle 3.0.2 pyhd3eb1b0_0
qstylizer 0.1.10 pyhd3eb1b0_0
qt 5.15.9 h06a4308_0
qt-main 5.15.2 h327a75a_7
qt-webengine 5.15.9 hd2b0992_4
qtawesome 1.0.3 pyhd3eb1b0_0
qtconsole 5.3.2 py39h06a4308_0
qtpy 2.2.0 py39h06a4308_0
qtwebkit 5.212 h4eab89a_4
queuelib 1.5.0 py39h06a4308_0
readline 8.1.2 h7f8727e_1
regex 2022.7.9 py39h5eee18b_0
requests 2.28.1 py39h06a4308_0
requests-file 1.5.1 pyhd3eb1b0_0
ripgrep 13.0.0 hbdeaff8_0
rope 0.22.0 pyhd3eb1b0_0
rtree 0.9.7 py39h06a4308_1
ruamel_yaml 0.15.100 py39h27cfd23_0
s3transfer 0.6.0 py39h06a4308_0
scikit-image 0.19.2 py39h51133e4_0
scikit-learn 1.0.2 py39h51133e4_1
scikit-learn-intelex 2021.6.0 py39h06a4308_0
scipy 1.9.1 py39h14f4228_0
scrapy 2.6.2 py39h06a4308_0
seaborn 0.11.2 pyhd3eb1b0_0
secretstorage 3.3.1 py39h06a4308_0
send2trash 1.8.0 pyhd3eb1b0_1
service_identity 18.1.0 pyhd3eb1b0_1
setuptools 63.4.1 py39h06a4308_0
sip 6.6.2 py39h6a678d5_0
six 1.16.0 pyhd3eb1b0_1
smart_open 5.2.1 py39h06a4308_0
snappy 1.1.9 h295c915_0
sniffio 1.2.0 py39h06a4308_1
snowballstemmer 2.2.0 pyhd3eb1b0_0
sortedcollections 2.1.0 pyhd3eb1b0_0
sortedcontainers 2.4.0 pyhd3eb1b0_0
soupsieve 2.3.1 pyhd3eb1b0_0
sphinx 5.0.2 py39h06a4308_0
sphinxcontrib-applehelp 1.0.2 pyhd3eb1b0_0
sphinxcontrib-devhelp 1.0.2 pyhd3eb1b0_0
sphinxcontrib-htmlhelp 2.0.0 pyhd3eb1b0_0
sphinxcontrib-jsmath 1.0.1 pyhd3eb1b0_0
sphinxcontrib-qthelp 1.0.3 pyhd3eb1b0_0
sphinxcontrib-serializinghtml 1.1.5 pyhd3eb1b0_0
spyder 5.3.3 py39h06a4308_0
spyder-kernels 2.3.3 py39h06a4308_0
sqlalchemy 1.4.39 py39h5eee18b_0
sqlite 3.39.3 h5082296_0
statsmodels 0.13.2 py39h7f8727e_0
sympy 1.10.1 py39h06a4308_0
tabulate 0.8.10 py39h06a4308_0
tbb 2021.6.0 hdb19cb5_0
tbb4py 2021.6.0 py39hdb19cb5_0
tblib 1.7.0 pyhd3eb1b0_0
tenacity 8.0.1 py39h06a4308_1
terminado 0.13.1 py39h06a4308_0
testpath 0.6.0 py39h06a4308_0
text-unidecode 1.3 pyhd3eb1b0_0
textdistance 4.2.1 pyhd3eb1b0_0
threadpoolctl 2.2.0 pyh0d69192_0
three-merge 0.1.1 pyhd3eb1b0_0
tifffile 2021.7.2 pyhd3eb1b0_2
tinycss 0.4 pyhd3eb1b0_1002
tk 8.6.12 h1ccaba5_0
tldextract 3.2.0 pyhd3eb1b0_0
toml 0.10.2 pyhd3eb1b0_0
tomli 2.0.1 py39h06a4308_0
tomlkit 0.11.1 py39h06a4308_0
toolz 0.11.2 pyhd3eb1b0_0
tornado 6.1 py39h27cfd23_0
tqdm 4.64.1 py39h06a4308_0
traitlets 5.1.1 pyhd3eb1b0_0
twisted 22.2.0 py39h5eee18b_1
typing-extensions 4.3.0 py39h06a4308_0
typing_extensions 4.3.0 py39h06a4308_0
tzdata 2022c h04d1e81_0
ujson 5.4.0 py39h6a678d5_0
unidecode 1.2.0 pyhd3eb1b0_0
unixodbc 2.3.11 h5eee18b_0
urllib3 1.26.11 py39h06a4308_0
w3lib 1.21.0 pyhd3eb1b0_0
watchdog 2.1.6 py39h06a4308_0
wcwidth 0.2.5 pyhd3eb1b0_0
webencodings 0.5.1 py39h06a4308_1
websocket-client 0.58.0 py39h06a4308_4
werkzeug 2.0.3 pyhd3eb1b0_0
wget 1.21.3 h0b77cf5_0
whatthepatch 1.0.2 py39h06a4308_0
wheel 0.37.1 pyhd3eb1b0_0
widgetsnbextension 3.5.2 py39h06a4308_0
wrapt 1.14.1 py39h5eee18b_0
wurlitzer 3.0.2 py39h06a4308_0
xarray 0.20.1 pyhd3eb1b0_1
xlrd 2.0.1 pyhd3eb1b0_0
xlsxwriter 3.0.3 pyhd3eb1b0_0
xz 5.2.6 h5eee18b_0
yaml 0.2.5 h7b6447c_0
yapf 0.31.0 pyhd3eb1b0_0
zeromq 4.3.4 h2531618_0
zfp 0.5.5 h295c915_6
zict 2.1.0 py39h06a4308_0
zipp 3.8.0 py39h06a4308_0
zlib 1.2.12 h5eee18b_3
zope 1.0 py39h06a4308_1
zope.interface 5.4.0 py39h7f8727e_0
zstd 1.5.2 ha4553b6_0
Mylszd
commented
1 year ago @milesp-nvidia here is the results:
**git***
Not inside a git repository
***OS Information***
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=20.04
DISTRIB_CODENAME=focal
DISTRIB_DESCRIPTION="Ubuntu 20.04.4 LTS"
NAME="Ubuntu"
VERSION="20.04.4 LTS (Focal Fossa)"
ID=ubuntu
ID_LIKE=debian
PRETTY_NAME="Ubuntu 20.04.4 LTS"
VERSION_ID="20.04"
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
VERSION_CODENAME=focal
UBUNTU_CODENAME=focal
Linux a4ae1cb36c17 5.4.0-117-generic #132~18.04.1-Ubuntu SMP Thu Jun 2 23:36:48 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux
***GPU Information***
Wed Jan 11 13:49:16 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.73.08 Driver Version: 510.73.08 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:02:00.0 On | N/A |
| 32% 43C P8 18W / 250W | 648MiB / 11264MiB | 4% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 NVIDIA GeForce ... Off | 00000000:03:00.0 Off | N/A |
| 29% 31C P8 9W / 250W | 11MiB / 11264MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
***CPU***
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 46 bits physical, 48 bits virtual
CPU(s): 12
On-line CPU(s) list: 0-11
Thread(s) per core: 2
Core(s) per socket: 6
Socket(s): 1
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 79
Model name: Intel(R) Core(TM) i7-6850K CPU @ 3.60GHz
Stepping: 1
CPU MHz: 1200.047
CPU max MHz: 4000.0000
CPU min MHz: 1200.0000
BogoMIPS: 7199.43
Virtualization: VT-x
L1d cache: 192 KiB
L1i cache: 192 KiB
L2 cache: 1.5 MiB
L3 cache: 15 MiB
NUMA node0 CPU(s): 0-11
Vulnerability Itlb multihit: KVM: Mitigation: Split huge pages
Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT vulnerable
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a rdseed adx smap intel_pt xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts md_clear flush_l1d
***CMake***
/opt/conda/bin/cmake
cmake version 3.23.3
CMake suite maintained and supported by Kitware (kitware.com/cmake).
***g++***
/usr/bin/g++
g++ (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
***nvcc***
/usr/local/cuda/bin/nvcc
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Jun__8_16:49:14_PDT_2022
Cuda compilation tools, release 11.7, V11.7.99
Build cuda_11.7.r11.7/compiler.31442593_0
***Python***
/opt/conda/bin/python
Python 3.8.13
***Environment Variables***
PATH : /usr/local/nvm/versions/node/v16.15.1/bin:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/bin:/opt/conda/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
LD_LIBRARY_PATH : /opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
NUMBAPRO_NVVM :
NUMBAPRO_LIBDEVICE :
CONDA_PREFIX :
PYTHON_PATH :
***conda packages***
/opt/conda/bin/conda
# packages in environment at /opt/conda:
#
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_kmp_llvm conda-forge
absl-py 1.2.0 pypi_0 pypi
aiohttp 3.8.3 pypi_0 pypi
aiosignal 1.3.1 pypi_0 pypi
alabaster 0.7.12 pypi_0 pypi
anyio 3.6.2 pypi_0 pypi
apex 0.1 pypi_0 pypi
appdirs 1.4.4 pypi_0 pypi
argon2-cffi 21.3.0 pypi_0 pypi
argon2-cffi-bindings 21.2.0 pypi_0 pypi
asttokens 2.0.5 pyhd8ed1ab_0 conda-forge
async-property 0.2.1 pypi_0 pypi
async-timeout 4.0.2 pypi_0 pypi
attrs 22.1.0 pypi_0 pypi
audioread 2.1.9 pypi_0 pypi
babel 2.10.3 pypi_0 pypi
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 py_2 conda-forge
backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
beautifulsoup4 4.11.1 pyha770c72_0 conda-forge
bleach 5.0.1 pypi_0 pypi
brotlipy 0.7.0 py38h0a891b7_1004 conda-forge
bzip2 1.0.8 h7f98852_4 conda-forge
c-ares 1.18.1 h7f98852_0 conda-forge
ca-certificates 2022.6.15 ha878542_0 conda-forge
cachetools 5.2.0 pypi_0 pypi
catalogue 2.0.6 py38h578d9bd_2 conda-forge
certifi 2022.6.15 py38h578d9bd_0 conda-forge
cffi 1.15.1 py38h4a40e3a_0 conda-forge
chardet 5.0.0 py38h578d9bd_0 conda-forge
charset-normalizer 2.1.0 pyhd8ed1ab_0 conda-forge
click 8.0.4 pypi_0 pypi
cloudpickle 2.1.0 pypi_0 pypi
cmake 3.23.3 h5432695_0 conda-forge
codecov 2.1.12 pypi_0 pypi
colorama 0.4.5 pyhd8ed1ab_0 conda-forge
conda 4.13.0 py38h578d9bd_1 conda-forge
conda-build 3.21.9 py38h578d9bd_1 conda-forge
conda-package-handling 1.8.1 py38h0a891b7_1 conda-forge
coverage 6.4.2 pypi_0 pypi
cryptography 37.0.4 py38h2b5fc30_0 conda-forge
cuda-python 11.6.0 pypi_0 pypi
cudf 22.6.0a0+319.g97422602b8 pypi_0 pypi
cugraph 22.6.0a0+114.gc6bc8867 pypi_0 pypi
cuml 22.6.0a0+71.g59a124168 pypi_0 pypi
cupy-cuda115 10.5.0 pypi_0 pypi
cycler 0.11.0 pypi_0 pypi
cymem 2.0.6 py38hfa26641_3 conda-forge
cython 0.29.32 pypi_0 pypi
cython-bbox 0.1.3 dev_0
cython-blis 0.7.8 py38h71d37f0_0 conda-forge
dask 2022.5.2 pypi_0 pypi
dask-cuda 22.6.0 pypi_0 pypi
dask-cudf 22.6.0a0+319.g97422602b8 pypi_0 pypi
dataclasses 0.8 pyhc8e2a94_3 conda-forge
debugpy 1.6.2 pypi_0 pypi
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pypi_0 pypi
distributed 2022.5.2 pypi_0 pypi
docutils 0.17.1 pypi_0 pypi
easydict 1.10 pypi_0 pypi
entrypoints 0.3 pypi_0 pypi
executing 0.9.1 pyhd8ed1ab_0 conda-forge
expat 2.4.8 h27087fc_0 conda-forge
expecttest 0.1.3 pypi_0 pypi
fastapi 0.88.0 pypi_0 pypi
fastjsonschema 2.16.1 pypi_0 pypi
fastrlock 0.8 pypi_0 pypi
filelock 3.7.1 pyhd8ed1ab_0 conda-forge
flake8 3.7.9 pypi_0 pypi
flask 2.2.1 pypi_0 pypi
fonttools 4.34.4 pypi_0 pypi
frozenlist 1.3.3 pypi_0 pypi
fsspec 2022.7.1 pypi_0 pypi
future 0.18.2 pypi_0 pypi
glob2 0.7 py_0 conda-forge
google-auth 2.9.1 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
graphsurgeon 0.4.6 pypi_0 pypi
grpcio 1.47.0 pypi_0 pypi
h11 0.14.0 pypi_0 pypi
heapdict 1.0.1 pypi_0 pypi
hypothesis 4.50.8 pypi_0 pypi
icu 70.1 h27087fc_0 conda-forge
idna 3.3 pyhd8ed1ab_0 conda-forge
imagesize 1.4.1 pypi_0 pypi
importlib-metadata 4.12.0 pypi_0 pypi
importlib-resources 5.9.0 pypi_0 pypi
iniconfig 1.1.1 pypi_0 pypi
iopath 0.1.10 pypi_0 pypi
ipykernel 6.15.1 pypi_0 pypi
ipython 8.4.0 py38h578d9bd_0 conda-forge
ipython-genutils 0.2.0 pypi_0 pypi
itsdangerous 2.1.2 pypi_0 pypi
jedi 0.18.1 py38h578d9bd_1 conda-forge
jinja2 3.1.2 pyhd8ed1ab_1 conda-forge
joblib 1.1.0 pypi_0 pypi
json5 0.9.9 pypi_0 pypi
jsonpatch 1.32 pypi_0 pypi
jsonpointer 2.3 pypi_0 pypi
jsonschema 4.9.1 pypi_0 pypi
jupyter-client 7.3.4 pypi_0 pypi
jupyter-core 4.11.1 pypi_0 pypi
jupyter-tensorboard 0.2.0 pypi_0 pypi
jupyterlab 2.3.2 pypi_0 pypi
jupyterlab-pygments 0.2.2 pypi_0 pypi
jupyterlab-server 1.2.0 pypi_0 pypi
jupytext 1.14.1 pypi_0 pypi
keyutils 1.6.1 h166bdaf_0 conda-forge
kiwisolver 1.4.4 pypi_0 pypi
krb5 1.19.3 h3790be6_0 conda-forge
langcodes 3.3.0 pyhd8ed1ab_0 conda-forge
lap 0.4.0 pypi_0 pypi
ld_impl_linux-64 2.36.1 hea4e1c9_2 conda-forge
libarchive 3.5.2 hb890918_3 conda-forge
libblas 3.9.0 15_linux64_openblas conda-forge
libcblas 3.9.0 15_linux64_openblas conda-forge
libcurl 7.83.1 h7bff187_0 conda-forge
libedit 3.1.20191231 he28a2e2_2 conda-forge
libev 4.33 h516909a_1 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc-ng 12.1.0 h8d9b700_16 conda-forge
libgfortran-ng 12.1.0 h69a702a_16 conda-forge
libgfortran5 12.1.0 hdcd56e2_16 conda-forge
libgomp 12.1.0 h8d9b700_16 conda-forge
libiconv 1.16 h516909a_0 conda-forge
liblapack 3.9.0 15_linux64_openblas conda-forge
liblief 0.11.5 h9c3ff4c_1 conda-forge
libllvm10 10.0.1 he513fc3_3 conda-forge
libnghttp2 1.47.0 h727a467_0 conda-forge
libnsl 2.0.0 h7f98852_0 conda-forge
libopenblas 0.3.20 pthreads_h78a6416_1 conda-forge
librosa 0.9.2 pypi_0 pypi
libssh2 1.10.0 ha56f1ee_2 conda-forge
libstdcxx-ng 12.1.0 ha89aaad_16 conda-forge
libuuid 2.32.1 h7f98852_1000 conda-forge
libuv 1.44.2 h166bdaf_0 conda-forge
libxml2 2.9.14 h22db469_3 conda-forge
libzlib 1.2.12 h166bdaf_2 conda-forge
llvm-openmp 14.0.4 he0ac6c6_0 conda-forge
llvmlite 0.39.0 pypi_0 pypi
lmdb 1.3.0 pypi_0 pypi
locket 1.0.0 pypi_0 pypi
lz4-c 1.9.3 h9c3ff4c_1 conda-forge
lzo 2.10 h516909a_1000 conda-forge
markdown 3.4.1 pypi_0 pypi
markdown-it-py 2.1.0 pypi_0 pypi
markupsafe 2.1.1 py38h0a891b7_1 conda-forge
matplotlib 3.5.2 pypi_0 pypi
matplotlib-inline 0.1.3 pyhd8ed1ab_0 conda-forge
mccabe 0.6.1 pypi_0 pypi
mdit-py-plugins 0.3.0 pypi_0 pypi
mdurl 0.1.1 pypi_0 pypi
mistune 0.8.4 pypi_0 pypi
mkl 2020.4 h726a3e6_304 conda-forge
mkl-include 2020.4 h726a3e6_304 conda-forge
mock 4.0.3 py38h578d9bd_3 conda-forge
msgpack 1.0.4 pypi_0 pypi
multidict 6.0.4 pypi_0 pypi
murmurhash 1.0.7 py38hfa26641_0 conda-forge
nbclient 0.6.6 pypi_0 pypi
nbconvert 6.5.0 pypi_0 pypi
nbformat 5.4.0 pypi_0 pypi
ncurses 6.3 h27087fc_1 conda-forge
nest-asyncio 1.5.5 pypi_0 pypi
networkx 2.6.3 pypi_0 pypi
ninja 1.11.0 h924138e_0 conda-forge
nltk 3.7 pypi_0 pypi
notebook 6.4.10 pypi_0 pypi
numba 0.56.0 pypi_0 pypi
numpy 1.22.4 py38h99721a1_0 conda-forge
nvcv-python 0.2.0a0 pypi_0 pypi
nvidia-dali-cuda110 1.16.0 pypi_0 pypi
nvidia-pyindex 1.0.9 pypi_0 pypi
nvtx 0.2.5 pypi_0 pypi
oauthlib 3.2.0 pypi_0 pypi
onnx 1.12.0 pypi_0 pypi
openblas 0.3.20 pthreads_h320a7e8_1 conda-forge
openssl 1.1.1q h166bdaf_0 conda-forge
packaging 21.3 pyhd8ed1ab_0 conda-forge
pandas 1.4.3 pypi_0 pypi
pandocfilters 1.5.0 pypi_0 pypi
parso 0.8.3 pyhd8ed1ab_0 conda-forge
partd 1.2.0 pypi_0 pypi
patch 2.7.6 h7f98852_1002 conda-forge
patchelf 0.15.0 h58526e2_0 conda-forge
pathy 0.6.2 pyhd8ed1ab_0 conda-forge
pexpect 4.8.0 pyh9f0ad1d_2 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 9.0.1 pypi_0 pypi
pip 21.2.4 pyhd8ed1ab_0 conda-forge
pkginfo 1.8.3 pyhd8ed1ab_0 conda-forge
pkgutil-resolve-name 1.3.10 pypi_0 pypi
pluggy 1.0.0 pypi_0 pypi
polygraphy 0.33.0 pypi_0 pypi
pooch 1.6.0 pypi_0 pypi
portalocker 2.5.1 pypi_0 pypi
preshed 3.0.6 py38hfa26641_2 conda-forge
prettytable 3.3.0 pypi_0 pypi
prometheus-client 0.14.1 pypi_0 pypi
prompt-toolkit 3.0.30 pyha770c72_0 conda-forge
protobuf 3.20.1 pypi_0 pypi
psutil 5.9.1 py38h0a891b7_0 conda-forge
ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
py 1.11.0 pypi_0 pypi
py-lief 0.11.5 py38h709712a_1 conda-forge
pyarrow 7.0.0 pypi_0 pypi
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pybind11 2.10.0 pypi_0 pypi
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mkhadatare
commented
1 year ago Hi @wzw773828204 Can you verify that all steps mentioned here - Samples works.
zhuyglx
commented
1 year ago have you solved this problem?
saikrishna2893
commented
1 year ago @milesp-nvidia We too face the same problem while testing the cropandresize application from the samples. Got the binary built. Imported the paths for the cvcuda .so files. Execution works fine till NVdecoder.
Following is the error being faced.
Hardware Decoder not supported. Falling back to default backend Processing: ../../assets/images/tabby_tiger_cat.jpg Processing: ../../assets/images/peoplenet.jpg Total decoding time: 0.00756531 (s) Avg decoding time per image: 0.00378266 (s) Avg images per sec: 264.365 Avg decoding time per batch: 0.00756531 (s) Line 62: '' failed: no kernel image is available for execution on the device Aborted (core dumped)
Any way to test a single cvcuda operation. Want to check the build and use the operations of CVCUDA. Thanks
Attaching the environment details for information:
`Click here to see environment details
**git***
commit f6ba577eba0d8e15a38c33ff5db265354caf92ad (HEAD, tag: v0.3.0-beta, origin/main, tags, tag, main)
Author: Miles Price <milesp@nvidia.com>
Date: Thu May 4 12:23:44 2023 -0700
fix: missing model code for CV-CUDA Release 0.3.0 Beta
**git submodules***
ca4d00ad3e2e0f410eeab3264d21b8a39397f362 3rdparty/dlpack (v0.8-1-gca4d00a)
5ab508a01f9eb089207ee87fd547d290da39d015 3rdparty/googletest (release-1.8.0-3127-g5ab508a0)
0694ec6a15863bff2e0ea5efe07c78de39b9a33c 3rdparty/pybind11 (v2.10.2)
***OS Information***
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=22.04
DISTRIB_CODENAME=jammy
DISTRIB_DESCRIPTION="Ubuntu 22.04.2 LTS"
PRETTY_NAME="Ubuntu 22.04.2 LTS"
NAME="Ubuntu"
VERSION_ID="22.04"
VERSION="22.04.2 LTS (Jammy Jellyfish)"
VERSION_CODENAME=jammy
ID=ubuntu
ID_LIKE=debian
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
UBUNTU_CODENAME=jammy
Linux 708c8205dcfe 5.15.0-71-generic #78~20.04.1-Ubuntu SMP Wed Apr 19 11:26:48 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux
***GPU Information***
Wed May 17 04:19:07 2023
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 530.30.02 Driver Version: 530.30.02 CUDA Version: 12.1 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
| 0 NVIDIA TITAN X (Pascal) On | 00000000:06:00.0 Off | N/A |
| 23% 30C P8 8W / 250W| 6MiB / 12288MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
+---------------------------------------------------------------------------------------+
***CPU***
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 39 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 4
On-line CPU(s) list: 0-3
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i5-4440 CPU @ 3.10GHz
CPU family: 6
Model: 60
Thread(s) per core: 1
Core(s) per socket: 4
Socket(s): 1
Stepping: 3
CPU max MHz: 3300.0000
CPU min MHz: 800.0000
BogoMIPS: 6196.23
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt dtherm ida arat pln pts md_clear flush_l1d
L1d cache: 128 KiB (4 instances)
L1i cache: 128 KiB (4 instances)
L2 cache: 1 MiB (4 instances)
L3 cache: 6 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-3
Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported
Vulnerability L1tf: Mitigation; PTE Inversion
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT disabled
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Unknown: No mitigations
Vulnerability Retbleed: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Mitigation; Microcode
Vulnerability Tsx async abort: Not affected
***CMake***
/usr/local/bin/cmake
cmake version 3.26.3
CMake suite maintained and supported by Kitware (kitware.com/cmake).
***g++***
/usr/bin/g++
g++ (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0
Copyright (C) 2021 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
***nvcc***
/usr/local/cuda/bin/nvcc
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Tue_Feb__7_19:32:13_PST_2023
Cuda compilation tools, release 12.1, V12.1.66
Build cuda_12.1.r12.1/compiler.32415258_0
***Python***
***Environment Variables***
PATH : /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
LD_LIBRARY_PATH : /usr/local/nvidia/lib:/usr/local/nvidia/lib64
NUMBAPRO_NVVM :
NUMBAPRO_LIBDEVICE :
CONDA_PREFIX :
PYTHON_PATH :
conda not found
***pip packages***
/usr/bin/pip
Package Version
------------------------ ----------
cfgv 3.3.1
cmake 3.26.3
distlib 0.3.4
filelock 3.6.0
identify 2.4.10
importlib-metadata 4.6.4
Jinja2 3.1.2
lit 16.0.3
MarkupSafe 2.1.2
more-itertools 8.10.0
mpmath 1.3.0
networkx 3.1
nodeenv 0.13.4
numpy 1.24.3
nvidia-cublas-cu11 11.10.3.66
nvidia-cuda-cupti-cu11 11.7.101
nvidia-cuda-nvrtc-cu11 11.7.99
nvidia-cuda-runtime-cu11 11.7.99
nvidia-cudnn-cu11 8.5.0.96
nvidia-cufft-cu11 10.9.0.58
nvidia-curand-cu11 10.2.10.91
nvidia-cusolver-cu11 11.4.0.1
nvidia-cusparse-cu11 11.7.4.91
nvidia-nccl-cu11 2.14.3
nvidia-nvtx-cu11 11.7.91
pip 22.0.2
platformdirs 2.5.1
pre-commit 2.17.0
PyYAML 5.4.1
setuptools 59.6.0
six 1.16.0
sympy 1.12
toml 0.10.2
torch 2.0.1
triton 2.0.0
typing_extensions 4.5.0
virtualenv 20.13.0+ds
wheel 0.37.1
zipp 1.0.0`
jony5017
commented
1 year ago I tried both on GPU 1070 and 3090 with the same CUDA version 11.7, but it only works on the 3090. So, I think cv-cuda is not compatible with the 1070 or other GPUs released around the same time.
AnimeDalit97
commented
1 year ago I tried both on GPU 1070 and 3090 with the same CUDA version 11.7, but it only works on the 3090. So, I think cv-cuda is not compatible with the 1070 or other GPUs released around the same time.
The compute capability of 10 series or titan X is 6.1, see here we can see cvcuda is only compiled for the devices whose cc>=7.0, see here
maybe you can add 61-real to fix it, but I'm not sure if there are any feature only supported by the devices whose cc >= 7.0
E.g.
list(APPEND CMAKE_CUDA_ARCHITECTURES
61-real
70-real # Volta - gv100/Tesla
75-real # Turing - tu10x/GeForce
80-real # Ampere - ga100/Tesla
86-real # Ampere - ga10x/GeForce
)Hi, In recent testing we didn't encounter this issue. Please open a new issue with additional details.
tp-nan
commented
10 months ago I tried both on GPU 1070 and 3090 with the same CUDA version 11.7, but it only works on the 3090. So, I think cv-cuda is not compatible with the 1070 or other GPUs released around the same time.
The compute capability of 10 series or titan X is 6.1, see here we can see cvcuda is only compiled for the devices whose cc>=7.0, see here
maybe you can add
61-realto fix it, but I'm not sure if there are any feature only supported by the devices whose cc >= 7.0 E.g.list(APPEND CMAKE_CUDA_ARCHITECTURES 61-real 70-real # Volta - gv100/Tesla 75-real # Turing - tu10x/GeForce 80-real # Ampere - ga100/Tesla 86-real # Ampere - ga10x/GeForce )
That's right. In order to provide a reference for those who encounter this issue again， I modified a version for Pascal(SM>=6.1) https://github.com/torchpipe/CV-CUDA
环境：
torch cu11.7
ubuntu20.04
显卡1080ti
代码 import os os.environ["CUDA_VISIBLE_DEVICES"] = "0" import torch import cvcuda,nvcv import torchnvjpeg
print("torch.cuda.is_available():",torch.cuda.is_available()) image_path = "./CV-CUDA-0.2.0-alpha/data/images/1.jpg" decoder = torchnvjpeg.Decoder()
image_data = open(image_path, 'rb').read()
image_tensor = decoder.decode(image_data) # run on GPU data_list = [imagetensor for in range(1)] print(image_tensor.shape)
image_tensors = torch.stack(data_list)
image_tensors_nchw = image_tensors.permute(0, 3, 1, 2) # from NHWC to NCHW
print(image_tensors_nchw.shape)
input_image_height, input_image_width = ( image_tensors.shape[1], image_tensors.shape[2], )
cvcuda_input_tensor = cvcuda.as_tensor(image_tensors, "NHWC") print("cvcuda_input_tensor.shape:",cvcuda_input_tensor.shape)
target_img_height=1920 target_img_width=1080
cvcuda_resized_tensor = cvcuda.resize( cvcuda_input_tensor, ( 1, target_img_height, target_img_width, 3, ), cvcuda.Interp.LINEAR, ) print("cvcuda_resized_tensor.shape:",cvcuda_resized_tensor.shape)