I am attempting to build a Docker image for deployment in JupyterHub using jupyter-repo2docker and the build is failing with the following error:
Encountered problems while solving.
Problem: package libgomp-9.3.0-h2828fa1_18 requires _libgcc_mutex 0.1 conda_forge, but none of the providers can be installed
Problem: package libgcc-ng-9.1.0-hdf63c60_0 requires _libgcc_mutex * main, but none of the providers can be installed
The following is the environment.yaml file used for this build. I exported it from the environment that I would like to replicate in JupyterHub. Note that I have tried adding conda-forge to the channels list and removing the environment name specification (line 1):
name: base
channels:
- defaults
dependencies:- conda-forge::_libgcc_mutex=0.1=main
- _tflow_select=2.1.0=gpu
- absl-py=0.12.0=py38h06a4308_0
- aio{removed}=3.7.4=py38h27cfd23_1
- astunparse=1.6.3=py_0
- async-timeout=3.0.1=py38h06a4308_0
- attrs=21.2.0=pyhd3eb1b0_0
- blas=1.0=mkl
- blinker=1.4=py38h06a4308_0
- brotlipy=0.7.0=py38h27cfd23_1003
- c-ares=1.17.1=h27cfd23_0
- ca-certificates=2021.4.13=h06a4308_1
- cachetools=4.2.2=pyhd3eb1b0_0
- certifi=2020.12.5=py38h06a4308_0
- cffi=1.14.3=py38h261ae71_2
- chardet=3.0.4=py38h06a4308_1003
- click=8.0.0=pyhd3eb1b0_0
- conda=4.10.1=py38h06a4308_1
- conda-package-handling=1.7.2=py38h03888b9_0
- coverage=5.5=py38h27cfd23_2
- cryptography=3.2.1=py38h3c74f83_1
- cudatoolkit=10.1.243=h6bb024c_0
- cudnn=7.6.5=cuda10.1_0
- cupti=10.1.168=0
- cython=0.29.23=py38h2531618_0
- gast=0.4.0=py_0
- google-auth=1.28.0=pyhd3eb1b0_0
- google-auth-oauthlib=0.4.4=pyhd3eb1b0_0
- google-pasta=0.2.0=py_0
- grpcio=1.36.1=py38h2157cd5_1
- h5py=2.10.0=py38hd6299e0_1
- hdf5=1.10.6=hb1b8bf9_0
- idna=2.10=py_0
- importlib-metadata=3.10.0=py38h06a4308_0
- intel-openmp=2021.2.0=h06a4308_610
- keras-preprocessing=1.1.2=pyhd3eb1b0_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
- libgfortran-ng=7.3.0=hdf63c60_0
- libprotobuf=3.14.0=h8c45485_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- markdown=3.3.4=py38h06a4308_0
- mkl=2021.2.0=h06a4308_296
- mkl-service=2.3.0=py38h27cfd23_1
- mkl_fft=1.3.0=py38h42c9631_2
- mkl_random=1.2.1=py38ha9443f7_2
- multidict=5.1.0=py38h27cfd23_2
- ncurses=6.2=he6710b0_1
- numpy=1.20.1=py38h93e21f0_0
- numpy-base=1.20.1=py38h7d8b39e_0
- oauthlib=3.1.0=py_0
- openssl=1.1.1k=h27cfd23_0
- opt_einsum=3.1.0=py_0
- pip=20.2.4=py38h06a4308_0
- protobuf=3.14.0=py38h2531618_1
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.8=py_0
- pycosat=0.6.3=py38h7b6447c_1
- pycparser=2.20=py_2
- pyjwt=1.7.1=py38_0
- pyopenssl=19.1.0=pyhd3eb1b0_1
- pysocks=1.7.1=py38h06a4308_0
- python=3.8.5=h7579374_1
- python-flatbuffers=1.12=pyhd3eb1b0_0
- readline=8.0=h7b6447c_0
- requests=2.24.0=py_0
- requests-oauthlib=1.3.0=py_0
- rsa=4.7.2=pyhd3eb1b0_1
- ruamel_yaml=0.15.87=py38h7b6447c_1
- scipy=1.6.2=py38had2a1c9_1
- setuptools=50.3.1=py38h06a4308_1
- six=1.15.0=py38h06a4308_0
- sqlite=3.33.0=h62c20be_0
- tensorboard=2.4.0=pyhc547734_0
- tensorboard-plugin-wit=1.6.0=py_0
- tensorflow=2.4.1=gpu_py38h8a7d6ce_0
- tensorflow-base=2.4.1=gpu_py38h29c2da4_0
- tensorflow-estimator=2.4.1=pyheb71bc4_0
- tensorflow-gpu=2.4.1=h30adc30_0
- termcolor=1.1.0=py38h06a4308_1
- tk=8.6.10=hbc83047_0
- tqdm=4.51.0=pyhd3eb1b0_0
- typing-extensions=3.7.4.3=hd3eb1b0_0
- typing_extensions=3.7.4.3=pyh06a4308_0
- urllib3=1.25.11=py_0
- werkzeug=1.0.1=pyhd3eb1b0_0
- wheel=0.35.1=pyhd3eb1b0_0
- wrapt=1.12.1=py38h7b6447c_1
- xz=5.2.5=h7b6447c_0
- yaml=0.2.5=h7b6447c_0
- yarl=1.6.3=py38h27cfd23_0
- zipp=3.4.1=pyhd3eb1b0_0
- zlib=1.2.11=h7b6447c_3
prefix: /root/miniconda3
Thanks for taking a look at this for me 