#A100ver
cluster_name = 'high-A100'
gpu_name = 'Standard_ND96asr_v4'
experiment_name = 'speaker_identification_training_A100'
hyperparameters = [
'--max_train_time', '172800'
script_folder = './script_folder'
# workspace
ws = Workspace.from_config()
print(ws.name, ws.location, ws.resource_group, sep='\t')
# compute cluster
compute_name = os.environ.get("AML_COMPUTE_CLUSTER_NAME", cluster_name)
compute_min_nodes = os.environ.get("AML_COMPUTE_CLUSTER_MIN_NODES", 0)
compute_max_nodes = os.environ.get("AML_COMPUTE_CLUSTER_MAX_NODES", 4)
vm_size = os.environ.get("AML_COMPUTE_CLUSTER_SKU", gpu_name)
if compute_name in ws.compute_targets:
compute_target = ws.compute_targets[compute_name]
if compute_target and type(compute_target) is AmlCompute:
print('found compute target. just use it. ' + compute_name)
else:
print('creating a new compute target...')
provisioning_config = AmlCompute.provisioning_configuration(vm_size=vm_size,
min_nodes=compute_min_nodes,
max_nodes=compute_max_nodes)
compute_target = ComputeTarget.create(
ws, compute_name, provisioning_config)
env = Environment.load_from_directory(path="./.azureml6/")
exp = Experiment(workspace=ws,name=experiment_name)
command = "pwd && pip install azure-storage-blob && python main.py"
# run
src = ScriptRunConfig(source_directory=script_folder,
command=command,
compute_target=compute_target,
environment=env
run = exp.submit(config=src)
Actually I found that in order to use A100, pytoch version should be 1.8.1+cu111. But by implementing conda install pytorch==1.8.1 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge, I got the error like below
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: |
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
pytorch==1.8.1 -> python[version='2.7.|3.5.|3.6.|3.6.12|3.6.12|3.7.10|3.7.10|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.5|>=3.7|>=3.6,<3.7|3.7.9|3.6.9|3.6.9|3.6.9|3.6.9|3.4.',build='1_73_pypy|2_73_pypy|3_73_pypy|4_73_pypy|1_73_pypy|0_73_pypy|5_73_pypy|5_73_pypy|0_73_pypy']
torchaudio==0.8.0 -> python[version='2.7.|3.5.|3.6.|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|3.4.|3.9.*']
Your python: python==3.7.9=h7579374_0
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package cudnn conflicts for:
torchvision==0.9.0 -> pytorch[version='>=1.8.0',build=cuda*] -> cudnn[version='>=8.2.1.32,<9.0a0']
torchvision==0.9.0 -> cudnn[version='>=7.6.5.32,<8.0a0|>=8.1.0.77,<9.0a0']
Package cudatoolkit conflicts for:
torchvision==0.9.0 -> cudatoolkit[version='10.2|10.2.|11.0|11.0.|11.1|11.1.|>=10.1,<10.2|>=10.2,<10.3|>=11.1,<11.2|11.2|11.2.']
torchaudio==0.8.0 -> pytorch==1.8.0 -> cudatoolkit[version='10.2|10.2.|11.0|11.0.|11.1|11.1.|11.2|11.2.|>=10.1,<10.2|>=11.1,<11.2|>=10.2,<10.3']
torchvision==0.9.0 -> cudnn[version='>=8.1.0.77,<9.0a0'] -> cudatoolkit[version='10.0|10.0.|10.1|10.1.|10.2.|11.|>=11.3,<11.4|9.2|9.2.*']
pytorch==1.8.1 -> cudatoolkit[version='>=10.1,<10.2|>=11.1,<11.2|>=10.2,<10.3']
Package libstdcxx-ng conflicts for:
python==3.7.9=h7579374_0 -> libffi[version='>=3.3,<3.4.0a0'] -> libstdcxx-ng[version='>=7.3.0|>=7.5.0']
torchaudio==0.8.0 -> numpy[version='>=1.11'] -> libstdcxx-ng[version='>=4.9|>=7.3.0|>=9.3.0|>=7.5.0|>=7.2.0']
torchvision==0.9.0 -> libstdcxx-ng[version='>=7.5.0']
torchvision==0.9.0 -> cudatoolkit[version='>=11.1,<11.2'] -> libstdcxx-ng[version='>=3.4|>=4.9|>=7.3.0|>=9.3.0|>=7.2.0']
pytorch==1.8.1 -> cudatoolkit[version='>=11.1,<11.2'] -> libstdcxx-ng[version='>=4.9|>=7.3.0|>=9.3.0|>=7.2.0']
pytorch==1.8.1 -> libstdcxx-ng[version='>=7.5.0']
cudatoolkit=11.1 -> libstdcxx-ng[version='>=9.3.0']
Package libgcc-ng conflicts for:
python==3.7.9=h7579374_0 -> libgcc-ng[version='>=7.3.0']
python==3.7.9=h7579374_0 -> libffi[version='>=3.3,<3.4.0a0'] -> libgcc-ng[version='>=4.9|>=7.5.0|>=9.4.0|>=9.3.0|>=7.2.0']
Package _libgcc_mutex conflicts for:
python==3.7.9=h7579374_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='|0.1|0.1',build='main|main|conda_forge']
cudatoolkit=11.1 -> libgcc-ng[version='>=9.3.0'] -> _libgcc_mutex[version='|0.1',build='main|main|conda_forge']
torchvision==0.9.0 -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='|0.1|0.1',build='main|main|conda_forge']
pytorch==1.8.1 -> _openmp_mutex -> _libgcc_mutex[version='|0.1',build='main|main|conda_forge']
Package pytorch conflicts for:
torchvision==0.9.0 -> pytorch[version='1.8.0|>=1.8.0|>=1.8.0',build='cuda*|cpu*']
torchaudio==0.8.0 -> pytorch==1.8.0
Package nccl conflicts for:
torchvision==0.9.0 -> pytorch==1.8.0 -> nccl[version='>=2.10.3.1,<3.0a0|>=2.7.8.1,<3.0a0|>=2.8.4.1,<3.0a0']
torchaudio==0.8.0 -> pytorch==1.8.0 -> nccl[version='>=2.7.8.1,<3.0a0|>=2.8.4.1,<3.0a0']
Package typing-extensions conflicts for:
pytorch==1.8.1 -> typing-extensions
torchvision==0.9.0 -> pytorch[version='>=1.8.0',build=cpu*] -> typing-extensionsThe following specifications were found to be incompatible with your system:
feature:/linux-64::__glibc==2.27=0
feature:|@/linux-64::__glibc==2.27=0
cudatoolkit=11.1 -> __glibc[version='>=2.17,<3.0.a0']
cudatoolkit=11.1 -> libgcc-ng[version='>=9.3.0'] -> __glibc[version='>=2.17']
pytorch==1.8.1 -> cudatoolkit[version='>=11.1,<11.2'] -> __glibc[version='>=2.17|>=2.17,<3.0.a0']
torchaudio==0.8.0 -> pytorch==1.8.0 -> __glibc[version='>=2.17|>=2.17,<3.0.a0']
torchvision==0.9.0 -> __glibc[version='>=2.17|>=2.17,<3.0.a0']
Your installed version is: 2.27
Can I solve this problem by adjusting the environment? or should I give up using A100?
Thank you so much
Please ignore the first
so I visited https://pytorch.org/get-started/locally/ and followed to implement conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch but it doesn't work. Neither did conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia
and warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))
@futo.mitsuishi Thanks for the question. Can you please add more details about the steps that you performed and also the python version. Did you use the Anaconda environment.
Can you share the Listing environments:
conda info --envs
bleach=3.3.1=pyhd3eb1b0_0
ca-certificates=2021.7.5=h06a4308_1
certifi=2021.5.30=py37h06a4308_0
cffi=1.14.6=py37h400218f_0
cycler=0.10.0=py37_0
dbus=1.13.18=hb2f20db_0
defusedxml=0.7.1=pyhd3eb1b0_0
entrypoints=0.3=py37_0
expat=2.3.0=h2531618_2
fontconfig=2.13.1=h6c09931_0
freetype=2.10.4=h5ab3b9f_0
glib=2.68.1=h36276a3_0
gst-plugins-base=1.14.0=h8213a91_2
gstreamer=1.14.0=h28cd5cc_2
icu=58.2=he6710b0_3
importlib_metadata=3.10.0=hd3eb1b0_0
intel-openmp=2021.2.0=h06a4308_610
ipykernel=5.3.4=py37h5ca1d4c_0
ipython_genutils=0.2.0=pyhd3eb1b0_1
jpeg=9b=h024ee3a_2
jsonschema=3.2.0=py_2
jupyter_client=6.1.12=pyhd3eb1b0_0
jupyter_core=4.7.1=py37h06a4308_0
jupyterlab_pygments=0.1.2=py_0
kiwisolver=1.3.1=py37h2531618_0
lcms2=2.12=h3be6417_0
ld_impl_linux-64=2.33.1=h53a641e_7
libedit=3.1.20191231=h14c3975_1
libffi=3.3=he6710b0_2
libgcc-ng=9.1.0=hdf63c60_0
libpng=1.6.37=hbc83047_0
libsodium=1.0.18=h7b6447c_0
libstdcxx-ng=9.1.0=hdf63c60_0
libtiff=4.1.0=h2733197_1
libuuid=1.0.3=h1bed415_2
libxcb=1.14=h7b6447c_0
libxml2=2.9.10=hb55368b_3
lz4-c=1.9.3=h2531618_0
markupsafe=1.1.1=py37h14c3975_1
matplotlib=3.3.4=py37h06a4308_0
matplotlib-base=3.3.4=py37h62a2d02_0
mistune=0.8.4=py37h14c3975_1001
mkl=2021.2.0=h06a4308_296
mkl-service=2.3.0=py37h27cfd23_1
mkl_fft=1.3.0=py37h42c9631_2
mkl_random=1.2.1=py37ha9443f7_2
nbclient=0.5.3=pyhd3eb1b0_0
nbconvert=6.1.0=py37h06a4308_0
nbformat=5.1.3=pyhd3eb1b0_0
ncurses=6.2=he6710b0_1
nest-asyncio=1.5.1=pyhd3eb1b0_0
notebook=6.4.0=py37h06a4308_0
olefile=0.46=py37_0
openjpeg=2.3.0=h05c96fa_1
openssl=1.1.1k=h27cfd23_0
pandocfilters=1.4.3=py37h06a4308_1
parso=0.8.2=pyhd3eb1b0_0
pcre=8.44=he6710b0_0
pickleshare=0.7.5=pyhd3eb1b0_1003
pip=20.2.4=py37_0
prometheus_client=0.11.0=pyhd3eb1b0_0
ptyprocess=0.7.0=pyhd3eb1b0_2
pycparser=2.20=py_2
pyparsing=2.4.7=pyhd3eb1b0_0
pyqt=5.9.2=py37h05f1152_2
pyrsistent=0.17.3=py37h7b6447c_0
python=3.7.9=h7579374_0
python-dateutil=2.8.1=pyhd3eb1b0_0
qt=5.9.7=h5867ecd_1
readline=8.0=h7b6447c_0
send2trash=1.5.0=pyhd3eb1b0_1
setuptools=50.3.0=py37hb0f4dca_1
sip=4.19.8=py37hf484d3e_0
six=1.15.0=py37h06a4308_0
sqlite=3.33.0=h62c20be_0
terminado=0.9.4=py37h06a4308_0
testpath=0.5.0=pyhd3eb1b0_0
tk=8.6.10=hbc83047_0
tornado=6.0.4=py37h7b6447c_1
traitlets=5.0.5=pyhd3eb1b0_0
wcwidth=0.2.5=py_0
webencodings=0.5.1=py37_1
wheel=0.35.1=py_0
xz=5.2.5=h7b6447c_0
zeromq=4.3.4=h2531618_0
zlib=1.2.11=h7b6447c_3
zstd=1.4.9=haebb681_0
absl-py==0.12.0
adal==1.2.7
alabaster==0.7.12
antlr4-python3-runtime==4.8
azure-common==1.1.27
azure-core==1.16.0
azure-graphrbac==0.61.1
azure-mgmt-authorization==0.61.0
azure-mgmt-containerregistry==8.0.0
azure-mgmt-core==1.3.0
azure-mgmt-keyvault==9.0.0
azure-mgmt-resource==13.0.0
azure-mgmt-storage==11.2.0
azureml-core==1.32.0
babel==2.9.0
backports-tempfile==1.0
backports-weakref==1.0.post1
boto3==1.9.246
botocore==1.12.246
cachetools==4.2.2
chardet==4.0.0
coloredlogs==14.0
contextlib2==0.6.0.post1
cryptography==3.4.7
datasets==1.4.1
decorator==5.0.7
dill==0.3.3
docformatter==1.3
docker==4.4.4
docutils==0.15.2
emoji==0.5.4
filelock==3.0.12
flake8==3.7.8
flake8-bugbear==19.8.0
fsspec==2021.4.0
fvcore==0.1.1.post20200716
gitdb2==2.0.5
gitpython==3.0.3
google-auth==1.30.0
google-auth-oauthlib==0.4.4
grpcio==1.37.0
huggingface-hub==0.0.2
humanfriendly==9.1
hydra-core==1.0.6
idna==2.10
imagesize==1.2.0
importlib-metadata==4.0.1
importlib-resources==5.1.2
ipython==7.19.0
isodate==0.6.0
jedi==0.18.0
jeepney==0.7.0
jinja2==2.11.3
jmespath==0.10.0
joblib==0.14.1
jsonlines==1.2.0
jsonpickle==2.0.0
markdown==3.3.4
markdown-it-py==0.5.8
mccabe==0.6.1
more-itertools==8.7.0
msrest==0.6.21
msrestazure==0.6.4
multiprocess==0.70.11.1
myst-parser==0.12.10
ndg-httpsclient==0.5.1
nltk==3.4.5
numpy==1.17.5
oauthlib==3.1.0
omegaconf==2.0.6
packaging==20.9
pandas==1.1.1
pathspec==0.8.1
pexpect==4.7.0
pillow==8.1.1
pluggy==0.13.1
portalocker==2.3.0
prompt-toolkit==3.0.18
protobuf==3.15.8
py==1.10.0
py-gfm==1.0.2
py-rouge==1.1
pyarrow==4.0.0
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycodestyle==2.5.0
pyflakes==2.1.1
pygments==2.8.1
pyjwt==2.1.0
pyopenssl==20.0.1
pytest==5.3.2
pytest-datadir==1.3.1
pytest-regressions==2.1.1
pytz==2021.1
pyyaml==5.4
pyzmq==18.1.0
regex==2020.1.8
requests==2.25.1
requests-mock==1.7.0
requests-oauthlib==1.3.0
rsa==4.7.2
ruamel-yaml==0.17.4
ruamel-yaml-clib==0.2.6
s3transfer==0.2.1
scikit-learn==0.23.1
scipy==1.4.1
secretstorage==3.3.1
sh==1.12.14
smmap==4.0.0
smmap2==3.0.1
snowballstemmer==2.1.0
sphinx==2.2.2
sphinx-autodoc-typehints==1.10.3
sphinx-rtd-theme==0.4.3
sphinxcontrib-applehelp==1.0.2
sphinxcontrib-devhelp==1.0.2
sphinxcontrib-htmlhelp==1.0.3
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==1.0.3
sphinxcontrib-serializinghtml==1.1.4
subword-nmt==0.3.7
tabulate==0.8.9
tensorboard==2.3.0
tensorboard-plugin-wit==1.8.0
tensorboardx==2.1
termcolor==1.1.0
threadpoolctl==2.1.0
tokenizers==0.10.2
torch==1.8.1
torchtext==0.9.1
tqdm==4.36.1
typing-extensions==3.7.4.1
unidecode==1.1.1
untokenize==0.1.1
urllib3==1.25.11
websocket-client==0.56.0
websocket-server==0.4
werkzeug==1.0.1
xxhash==2.0.2
yacs==0.1.8
zipp==3.4.1
I implemented conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch, and export to yml file.
Then in order to create job to computing cliuster I implemented below
#A100ver
cluster_name = 'high-A100'
gpu_name = 'Standard_ND96asr_v4'
experiment_name = 'speaker_identification_training_A100'
hyperparameters = [
'--max_train_time', '172800'
script_folder = './script_folder'
# workspace
ws = Workspace.from_config()
print(ws.name, ws.location, ws.resource_group, sep='\t')
# compute cluster
compute_name = os.environ.get("AML_COMPUTE_CLUSTER_NAME", cluster_name)
compute_min_nodes = os.environ.get("AML_COMPUTE_CLUSTER_MIN_NODES", 0)
compute_max_nodes = os.environ.get("AML_COMPUTE_CLUSTER_MAX_NODES", 4)
vm_size = os.environ.get("AML_COMPUTE_CLUSTER_SKU", gpu_name)
if compute_name in ws.compute_targets:
compute_target = ws.compute_targets[compute_name]
if compute_target and type(compute_target) is AmlCompute:
print('found compute target. just use it. ' + compute_name)
else:
print('creating a new compute target...')
provisioning_config = AmlCompute.provisioning_configuration(vm_size=vm_size,
min_nodes=compute_min_nodes,
max_nodes=compute_max_nodes)
compute_target = ComputeTarget.create(
ws, compute_name, provisioning_config)
env = Environment.load_from_directory(path="./.azureml6/")
exp = Experiment(workspace=ws,name=experiment_name)
command = "pwd && pip install azure-storage-blob && python main.py"
# run
src = ScriptRunConfig(source_directory=script_folder,
command=command,
compute_target=compute_target,
environment=env
run = exp.submit(config=src)
Actually I found that in order to use A100, pytoch version should be 1.8.1+cu111. But by implementing conda install pytorch==1.8.1 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge, I got the error like below
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: |
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
pytorch==1.8.1 -> python[version='2.7.|3.5.|3.6.|3.6.12|3.6.12|3.7.10|3.7.10|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.5|>=3.7|>=3.6,<3.7|3.7.9|3.6.9|3.6.9|3.6.9|3.6.9|3.4.',build='1_73_pypy|2_73_pypy|3_73_pypy|4_73_pypy|1_73_pypy|0_73_pypy|5_73_pypy|5_73_pypy|0_73_pypy']
torchaudio==0.8.0 -> python[version='2.7.|3.5.|3.6.|>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|3.4.|3.9.*']
Your python: python==3.7.9=h7579374_0
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package cudnn conflicts for:
torchvision==0.9.0 -> pytorch[version='>=1.8.0',build=cuda*] -> cudnn[version='>=8.2.1.32,<9.0a0']
torchvision==0.9.0 -> cudnn[version='>=7.6.5.32,<8.0a0|>=8.1.0.77,<9.0a0']
Package cudatoolkit conflicts for:
torchvision==0.9.0 -> cudatoolkit[version='10.2|10.2.|11.0|11.0.|11.1|11.1.|>=10.1,<10.2|>=10.2,<10.3|>=11.1,<11.2|11.2|11.2.']
torchaudio==0.8.0 -> pytorch==1.8.0 -> cudatoolkit[version='10.2|10.2.|11.0|11.0.|11.1|11.1.|11.2|11.2.|>=10.1,<10.2|>=11.1,<11.2|>=10.2,<10.3']
torchvision==0.9.0 -> cudnn[version='>=8.1.0.77,<9.0a0'] -> cudatoolkit[version='10.0|10.0.|10.1|10.1.|10.2.|11.|>=11.3,<11.4|9.2|9.2.*']
pytorch==1.8.1 -> cudatoolkit[version='>=10.1,<10.2|>=11.1,<11.2|>=10.2,<10.3']
Package libstdcxx-ng conflicts for:
python==3.7.9=h7579374_0 -> libffi[version='>=3.3,<3.4.0a0'] -> libstdcxx-ng[version='>=7.3.0|>=7.5.0']
torchaudio==0.8.0 -> numpy[version='>=1.11'] -> libstdcxx-ng[version='>=4.9|>=7.3.0|>=9.3.0|>=7.5.0|>=7.2.0']
torchvision==0.9.0 -> libstdcxx-ng[version='>=7.5.0']
torchvision==0.9.0 -> cudatoolkit[version='>=11.1,<11.2'] -> libstdcxx-ng[version='>=3.4|>=4.9|>=7.3.0|>=9.3.0|>=7.2.0']
pytorch==1.8.1 -> cudatoolkit[version='>=11.1,<11.2'] -> libstdcxx-ng[version='>=4.9|>=7.3.0|>=9.3.0|>=7.2.0']
pytorch==1.8.1 -> libstdcxx-ng[version='>=7.5.0']
cudatoolkit=11.1 -> libstdcxx-ng[version='>=9.3.0']
Package libgcc-ng conflicts for:
python==3.7.9=h7579374_0 -> libgcc-ng[version='>=7.3.0']
python==3.7.9=h7579374_0 -> libffi[version='>=3.3,<3.4.0a0'] -> libgcc-ng[version='>=4.9|>=7.5.0|>=9.4.0|>=9.3.0|>=7.2.0']
Package _libgcc_mutex conflicts for:
python==3.7.9=h7579374_0 -> libgcc-ng[version='>=7.3.0'] -> _libgcc_mutex[version='|0.1|0.1',build='main|main|conda_forge']
cudatoolkit=11.1 -> libgcc-ng[version='>=9.3.0'] -> _libgcc_mutex[version='|0.1',build='main|main|conda_forge']
torchvision==0.9.0 -> libgcc-ng[version='>=7.5.0'] -> _libgcc_mutex[version='|0.1|0.1',build='main|main|conda_forge']
pytorch==1.8.1 -> _openmp_mutex -> _libgcc_mutex[version='|0.1',build='main|main|conda_forge']
Package pytorch conflicts for:
torchvision==0.9.0 -> pytorch[version='1.8.0|>=1.8.0|>=1.8.0',build='cuda*|cpu*']
torchaudio==0.8.0 -> pytorch==1.8.0
Package nccl conflicts for:
torchvision==0.9.0 -> pytorch==1.8.0 -> nccl[version='>=2.10.3.1,<3.0a0|>=2.7.8.1,<3.0a0|>=2.8.4.1,<3.0a0']
torchaudio==0.8.0 -> pytorch==1.8.0 -> nccl[version='>=2.7.8.1,<3.0a0|>=2.8.4.1,<3.0a0']
Package typing-extensions conflicts for:
pytorch==1.8.1 -> typing-extensions
torchvision==0.9.0 -> pytorch[version='>=1.8.0',build=cpu*] -> typing-extensionsThe following specifications were found to be incompatible with your system:
feature:/linux-64::__glibc==2.27=0
feature:|@/linux-64::__glibc==2.27=0
cudatoolkit=11.1 -> __glibc[version='>=2.17,<3.0.a0']
cudatoolkit=11.1 -> libgcc-ng[version='>=9.3.0'] -> __glibc[version='>=2.17']
pytorch==1.8.1 -> cudatoolkit[version='>=11.1,<11.2'] -> __glibc[version='>=2.17|>=2.17,<3.0.a0']
torchaudio==0.8.0 -> pytorch==1.8.0 -> __glibc[version='>=2.17|>=2.17,<3.0.a0']
torchvision==0.9.0 -> __glibc[version='>=2.17|>=2.17,<3.0.a0']
Your installed version is: 2.27
Can I solve this problem by adjusting the environment? or should I give up using A100?
Thank you so much
