The problem on Installation
Hi, I tried to setup the base virtual environment, but I faced a problem.
$ conda env create -f semiseg.yaml
Then, I can see this message.
Collecting package metadata (repodata.json): done Solving environment: failed
ResolvePackageNotFound:
- jsonschema==2.6.0=py36_0
- libprotobuf==3.6.1=hd408876_0
- libarchive==3.3.3=h5d8350f_5
- lzo==2.10=h49e0be7_2
- kiwisolver==1.0.1=py36hf484d3e_0
- gmp==6.1.2=h6c8ec71_1
- fontconfig==2.13.0=h9420a91_0
- cudatoolkit==9.0=h13b8566_0
- lazy-object-proxy==1.3.1=py36h14c3975_2
- sip==4.19.8=py36hf484d3e_0
- lxml==4.2.5=py36hefd8a0e_0
- bzip2==1.0.6=h14c3975_5
- .....
- .
- .
- .
- .
- .
- . I skipped others since there are too many lines. Maybe almost dependency packages cannot be found.
My environment. Win10 Anaconda Version : 1.7.2 GPU: RTX3090
Please help me. Thank you.
Hi, which version of CUDA do you use? The commond is nvcc -V.
Hi, which version of CUDA do you use? The commond is
nvcc -V.
I have two workstations with different environment.
- GPU: RTX3090, CUDA version: 11.2.142
- GPU: V100, CUDA version: V10.0.130
thank you.
I could not find the problem according to the current information. Maybe you could install Apex first (Cuda 9 or Cuda 10 is recommended) and then manually install the libraries needed at runtime.
@openmll I'm sorry to bother you. Have you successfully run the program on win10 system? I also encountered the same problem on win10 system.
@charlesCXK Hi, I tried to setup the base virtual environment, but I faced a problem.

@ChrisLiang2020 Sorry, we didn't test the code on Win10. We recommend using Linux instead.
with linux i unfortunately get also a huge list of incompatabilities when trying to create the environment from yml:
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package send2trash conflicts for:
jupyter==1.0.0=py36_7 -> notebook -> send2trash[version='>=1.5.0|>=1.8.0']
widgetsnbextension==3.4.2=py36_0 -> notebook[version='>=4.4.1'] -> send2trash[version='>=1.5.0|>=1.8.0']
jupyterlab_server==0.2.0=py36_0 -> notebook -> send2trash[version='>=1.5.0|>=1.8.0']
send2trash==1.5.0=py36_0
jupyterlab_launcher==0.13.1=py36_0 -> notebook -> send2trash[version='>=1.5.0|>=1.8.0']
notebook==5.7.2=py36_0 -> send2trash
jupyterlab==0.35.3=py36_0 -> notebook[version='>=4.3.1'] -> send2trash[version='>=1.5.0|>=1.8.0']
Package _openmp_mutex conflicts for:
[..]
Hi, I'm also facing some conflict issues when trying to install the environment and was wondering if there was anything I could do to resolve the conflicts. I'm in a Linux environment, conda version 23.5.2 and Python 3.11.4. Please let me know if there is something I could do to resolve the issue. Thank you!
I get the following error:
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package jinja2 conflicts for: nbconvert==5.4.0=py36_1 -> jinja2 widgetsnbextension==3.4.2=py36_0 -> notebook[version='>=4.4.1'] -> jinja2 jinja2==2.10=py36_0 conda-build==3.17.3=py36_0 -> jinja2!=3.0.0 spyder==3.3.2=py36_0 -> nbconvert -> jinja2[version='>=2.10|>=2.4|>=3.0|>=2.3'] jupyterlab_server==0.2.0=py36_0 -> notebook -> jinja2 notebook==5.7.2=py36_0 -> nbconvert -> jinja2[version='>=2.4|>=3.0'] sphinx==1.8.2=py36_0 -> jinja2[version='>=2.3'] flask-cors==3.0.7=py36_0 -> flask[version='>=0.9'] -> jinja2[version='>=2.10,<3.0|>=2.10.1,<3.0|>=3.0|>=2.4'] jupyter==1.0.0=py36_7 -> nbconvert -> jinja2[version='>=2.4|>=3.0'] jupyterlab==0.35.3=py36_0 -> notebook[version='>=4.3.1'] -> jinja2 flask==1.0.2=py36_1 -> jinja2[version='>=2.10,<3.0'] _ipyw_jlab_nb_ext_conf==0.1.0=py36_0 -> jupyterlab -> jinja2[version='>=2.1|>=2.10'] notebook==5.7.2=py36_0 -> jinja2 numpydoc==0.8.0=py36_0 -> sphinx -> jinja2[version='>=2.3'] jupyterlab_launcher==0.13.1=py36_0 -> notebook -> jinja2
Package libgcc-ng conflicts for: alabaster==0.7.12=py36_0 -> python[version='>=3.6,<3.7.0a0'] -> libgcc-ng[version='>=7.2.0|>=7.3.0|>=7.5.0'] fastcache==1.0.2=py36h14c3975_2 -> libgcc-ng[version='>=7.2.0'] mkl_random==1.0.1=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> libgcc-ng[version='>=11.2.0|>=7.5.0|>=7.3.0'] [...]