pytorch version is too old?

[miziha-zp]

first, I download simclr pretrained model from SCAN repo, then I create and conda env using your provided requirements.yaml, last run your code by python simclr.py --config_env configs/env.yml --config_exp configs/pretext/simclr_cifar10.yml, some error raised like below.

Traceback (most recent call last):
  File "simclr.py", line 145, in <module>
    main()
  File "simclr.py", line 86, in main
    state = torch.load(p['pretext_model'], map_location='cpu')
  File "/data/zhousheng/anaconda3/envs/NNM/lib/python3.7/site-packages/torch/serialization.py", line 527, in load
    with _open_zipfile_reader(f) as opened_zipfile:
  File "/data/zhousheng/anaconda3/envs/NNM/lib/python3.7/site-packages/torch/serialization.py", line 224, in __init__
    super(_open_zipfile_reader, self).__init__(torch._C.PyTorchFileReader(name_or_buffer))
RuntimeError: version_ <= kMaxSupportedFileFormatVersion INTERNAL ASSERT FAILED at /opt/conda/conda-bld/pytorch_1579040055865/work/caffe2/serialize/inline_container.cc:132, please report a bug to PyTorch. Attempted to read a PyTorch file with version 3, but the maximum supported version for reading is 2. Your PyTorch installation may be too old. (init at /opt/conda/conda-bld/pytorch_1579040055865/work/caffe2/serialize/inline_container.cc:132)

[ZhiyuanDang]

Hi @miziha-zp ,

The version of the pytorch is the same as to SCAN method (1.4.0 and cuda 10.0.130).

Could you please provide more information, such as the conda env package list?

[miziha-zp]

thx for your reply, the conda list is below follow your requirement.yaml and the pretrained model download from https://drive.google.com/file/d/1Cl5oAcJKoNE5FSTZsBSAKLcyA5jXGgTT/view

# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: linux-64
_libgcc_mutex=0.1=main
blas=1.0=mkl
blis=0.4.1=pypi_0
bzip2=1.0.8=h7b6447c_0
ca-certificates=2020.1.1=0
cairo=1.14.12=h8948797_3
catalogue=1.0.0=pypi_0
certifi=2020.4.5.1=py37_0
cffi=1.14.0=py37h2e261b9_0
chardet=3.0.4=pypi_0
cmake=3.14.0=h52cb24c_0
cudatoolkit=10.0.130=0
cycler=0.10.0=py37_0
cymem=2.0.3=pypi_0
dbus=1.13.12=h746ee38_0
easydict=1.9=pypi_0
expat=2.2.6=he6710b0_0
faiss-gpu=1.6.3=py37h1a5d453_0
ffmpeg=4.0=hcdf2ecd_0
fontconfig=2.13.0=h9420a91_0
freeglut=3.0.0=hf484d3e_5
freetype=2.9.1=h8a8886c_1
glib=2.63.1=h5a9c865_0
graphite2=1.3.13=h23475e2_0
gst-plugins-base=1.14.0=hbbd80ab_1
gstreamer=1.14.0=hb453b48_1
h5py=2.8.0=py37h989c5e5_3
harfbuzz=1.8.8=hffaf4a1_0
hdf5=1.10.2=hba1933b_1
icu=58.2=h9c2bf20_1
idna=2.9=pypi_0
imageio=2.8.0=py_0
importlib-metadata=1.6.0=pypi_0
intel-openmp=2020.0=166
jasper=2.0.14=h07fcdf6_1
joblib=0.14.1=py_0
jpeg=9b=h024ee3a_2
kiwisolver=1.1.0=py37he6710b0_0
krb5=1.17.1=h173b8e3_0
ld_impl_linux-64=2.33.1=h53a641e_7
libcurl=7.69.1=h20c2e04_0
libedit=3.1.20181209=hc058e9b_0
libffi=3.2.1=hd88cf55_4
libgcc-ng=9.1.0=hdf63c60_0
libgfortran-ng=7.3.0=hdf63c60_0
libglu=9.0.0=hf484d3e_1
libopencv=3.4.2=hb342d67_1
libopus=1.3.1=h7b6447c_0
libpng=1.6.37=hbc83047_0
libprotobuf=3.11.4=hd408876_0
libssh2=1.9.0=h1ba5d50_1
libstdcxx-ng=9.1.0=hdf63c60_0
libtiff=4.1.0=h2733197_0
libuuid=1.0.3=h1bed415_2
libvpx=1.7.0=h439df22_0
libxcb=1.13=h1bed415_1
libxml2=2.9.9=hea5a465_1
matplotlib=3.1.3=py37_0
matplotlib-base=3.1.3=py37hef1b27d_0
mkl=2020.0=166
mkl-service=2.3.0=py37he904b0f_0
mkl_fft=1.0.15=py37ha843d7b_0
mkl_random=1.1.0=py37hd6b4f25_0
murmurhash=1.0.2=pypi_0
ncurses=6.2=he6710b0_0
ninja=1.9.0=py37hfd86e86_0
numpy=1.18.1=py37h4f9e942_0
numpy-base=1.18.1=py37hde5b4d6_1
olefile=0.46=py_0
opencv=3.4.2=py37h6fd60c2_1
openssl=1.1.1g=h7b6447c_0
pcre=8.43=he6710b0_0
pillow=7.0.0=py37hb39fc2d_0
pip=20.0.2=py37_1
pixman=0.38.0=h7b6447c_0
plac=1.1.3=pypi_0
preshed=3.0.2=pypi_0
protobuf=3.11.4=py37he6710b0_0
py-opencv=3.4.2=py37hb342d67_1
pycparser=2.20=py_0
pyparsing=2.4.6=py_0
pyqt=5.9.2=py37h05f1152_2
python=3.7.7=hcf32534_0_cpython
python-dateutil=2.8.1=py_0
pytorch=1.4.0=py3.7_cuda10.0.130_cudnn7.6.3_0
pyyaml=5.3.1=py37h7b6447c_0
qt=5.9.7=h5867ecd_1
readline=8.0=h7b6447c_0
requests=2.23.0=pypi_0
rhash=1.3.8=h1ba5d50_0
scikit-learn=0.22.1=py37hd81dba3_0
scipy=1.4.1=py37h0b6359f_0
setuptools=46.1.3=py37_0
sip=4.19.8=py37hf484d3e_0
six=1.14.0=py37_0
spacy=2.2.4=pypi_0
sqlite=3.31.1=h7b6447c_0
srsly=1.0.2=pypi_0
swig=3.0.12=h38cdd7d_3
tensorboardx=2.1=pypi_0
termcolor=1.1.0=py37_1
thinc=7.4.0=pypi_0
tk=8.6.8=hbc83047_0
torchvision=0.5.0=py37_cu100
tornado=6.0.4=py37h7b6447c_1
tqdm=4.45.0=pypi_0
typing=3.6.4=py37_0
urllib3=1.25.8=pypi_0
wasabi=0.6.0=pypi_0
wheel=0.34.2=py37_0
xz=5.2.4=h14c3975_4
yaml=0.1.7=had09818_2
zipp=3.1.0=pypi_0
zlib=1.2.11=h7b6447c_3
zstd=1.3.7=h0b5b093_0

[ZhiyuanDang]

These packages seem fine. To be honest, I never encounter this problem.

Maybe you forget to activate the conda env? Or have you tried to restart the shell?

Please consider typing print(torch.__version__) to display the version of pytorch in python shell.

[miziha-zp]

These packages seem fine. To be honest, I never encounter this problem.

Maybe you forget to activate the conda env? Or have you tried to restart the shell?

Please consider typing print(torch.__version__) to display the version of pytorch in python shell.

thanks again, I will try later on another machine, maybe the cuda deriver(11.1) is too new...

[ZhiyuanDang]

Maybe you workers on Ampere-based GPU, such as GeForce RTX 30XX, A100, etc.

These GPUs only support CUDA 11 and later versions.

Thanks for your attention to our work. I will close this issue.