I constantly get ResolvePackageNotFound

Question

When I type conda env create -f environment.yml

I constantly get

Collecting package metadata (repodata.json): done Solving environment: failed

ResolvePackageNotFound:
  - tk==8.6.8=hbc83047_0
  - zlib==1.2.11=h7b6447c_3
  - av==8.0.2=py37h06622b3_4
  - lame==3.100=h7f98852_1001
  - xz==5.2.4=h14c3975_4
  - mkl_random==1.0.2=py37hd81dba3_0
  - x264==1!152.20180806=h14c3975_0
  - numpy-base==1.16.4=py37hde5b4d6_0
  - certifi==2020.12.5=py37h06a4308_0
  - _openmp_mutex==4.5=1_llvm
  - llvm-openmp==11.0.0=hfc4b9b4_1
  - freetype==2.9.1=h8a8886c_1
  - scikit-learn==0.22.1=py37hd81dba3_0
  - libgfortran-ng==7.3.0=hdf63c60_0
  - readline==7.0=h7b6447c_5
  - mkl_fft==1.0.12=py37ha843d7b_0
  - libpng==1.6.37=hbc83047_0
  - libedit==3.1.20181209=hc058e9b_0
  - libffi==3.2.1=hd88cf55_4
  - nettle==3.6=he412f7d_0
  - gnutls==3.6.13=h85f3911_1
  - python==3.7.3=h0371630_0
  - gmp==6.2.1=h58526e2_0
  - _libgcc_mutex==0.1=conda_forge
  - libgcc-ng==9.3.0=h5dbcf3e_17
  - mkl-service==2.3.0=py37he904b0f_0
  - ffmpeg==4.3.1=h3215721_1
  - openh264==2.1.1=h8b12597_0
  - mkl==2019.4=243
  - numpy==1.16.4=py37h7e9f1db_0
  - ca-certificates==2020.12.8=h06a4308_0
  - libiconv==1.16=h516909a_0
  - intel-openmp==2019.4=243
  - libstdcxx-ng==9.1.0=hdf63c60_0
  - zstd==1.3.7=h0b5b093_0
  - ncurses==6.1=he6710b0_1
  - jpeg==9b=h024ee3a_2
  - openssl==1.1.1i=h27cfd23_0
  - bzip2==1.0.8=h7f98852_4
  - sqlite==3.28.0=h7b6447c_0
  - libtiff==4.0.10=h2733197_2

What should I do?

My yml file is:

name: StyleFlow
channels:
  - anaconda
  - defaults
  - conda-forge
dependencies:
  - _libgcc_mutex=0.1=conda_forge
  - _openmp_mutex=4.5=1_llvm
  - av=8.0.2=py37h06622b3_4
  - blas=1.0=mkl
  - bzip2=1.0.8=h7f98852_4
  - ca-certificates=2020.12.8=h06a4308_0
  - certifi=2020.12.5=py37h06a4308_0
  - ffmpeg=4.3.1=h3215721_1
  - freetype=2.9.1=h8a8886c_1
  - gmp=6.2.1=h58526e2_0
  - gnutls=3.6.13=h85f3911_1
  - intel-openmp=2019.4=243
  - joblib=0.14.1=py_0
  - jpeg=9b=h024ee3a_2
  - lame=3.100=h7f98852_1001
  - libedit=3.1.20181209=hc058e9b_0
  - libffi=3.2.1=hd88cf55_4
  - libgcc-ng=9.3.0=h5dbcf3e_17
  - libgfortran-ng=7.3.0=hdf63c60_0
  - libiconv=1.16=h516909a_0
  - libpng=1.6.37=hbc83047_0
  - libstdcxx-ng=9.1.0=hdf63c60_0
  - libtiff=4.0.10=h2733197_2
  - llvm-openmp=11.0.0=hfc4b9b4_1
  - mkl=2019.4=243
  - mkl-service=2.3.0=py37he904b0f_0
  - mkl_fft=1.0.12=py37ha843d7b_0
  - mkl_random=1.0.2=py37hd81dba3_0
  - natsort=6.0.0=py_0
  - ncurses=6.1=he6710b0_1
  - nettle=3.6=he412f7d_0
  - numpy=1.16.4=py37h7e9f1db_0
  - numpy-base=1.16.4=py37hde5b4d6_0
  - olefile=0.46=py37_0
  - openh264=2.1.1=h8b12597_0
  - openssl=1.1.1i=h27cfd23_0
  - pip=19.1.1=py37_0
  - python=3.7.3=h0371630_0
  - python_abi=3.7=1_cp37m
  - readline=7.0=h7b6447c_5
  - scikit-learn=0.22.1=py37hd81dba3_0
  - setuptools=41.0.1=py37_0
  - sqlite=3.28.0=h7b6447c_0
  - tk=8.6.8=hbc83047_0
  - wheel=0.33.4=py37_0
  - x264=1!152.20180806=h14c3975_0
  - xz=5.2.4=h14c3975_4
  - zlib=1.2.11=h7b6447c_3
  - zstd=1.3.7=h0b5b093_0
  - pip:
    - absl-py==0.7.1
    - appdirs==1.4.4
    - astor==0.8.0
    - astunparse==1.6.3
    - attrs==19.1.0
    - backcall==0.1.0
    - bleach==3.1.0
    - cachetools==4.1.0
    - cffi==1.12.3
    - chardet==3.0.4
    - cloudpickle==1.2.1
    - cycler==0.10.0
    - cytoolz==0.9.0.1
    - dask==2.1.0
    - decorator==4.4.0
    - defusedxml==0.6.0
    - deprecated==1.2.6
    - dill==0.2.9
    - dlib==19.21.0
    - dominate==2.3.5
    - easydict==1.9
    - entrypoints==0.3
    - gast==0.2.2
    - google-auth==1.14.3
    - google-auth-oauthlib==0.4.1
    - google-pasta==0.2.0
    - grpcio==1.22.0
    - h5py==2.10.0
    - helpdev==0.6.10
    - idna==2.8
    - imageio==2.5.0
    - importlib-metadata==0.18
    - imutils==0.5.3
    - ipykernel==5.1.1
    - ipython==7.6.0
    - ipython-genutils==0.2.0
    - ipywidgets==7.4.2
    - jedi==0.13.3
    - jinja2==2.10.1
    - jsonschema==3.0.1
    - jupyter==1.0.0
    - jupyter-client==5.2.4
    - jupyter-console==6.0.0
    - jupyter-core==4.5.0
    - keras==2.2.4
    - keras-applications==1.0.8
    - keras-preprocessing==1.1.0
    - kiwisolver==1.1.0
    - mako==1.1.2
    - markdown==3.1.1
    - markupsafe==1.1.1
    - matplotlib==3.1.0
    - mistune==0.8.4
    - nbconvert==5.5.0
    - nbformat==4.4.0
    - networkx==2.3
    - notebook==5.7.8
    - oauthlib==3.1.0
    - opencv-python==4.1.0.25
    - opt-einsum==3.2.1
    - pandocfilters==1.4.2
    - parso==0.5.0
    - pexpect==4.7.0
    - pickleshare==0.7.5
    - pillow==6.0.0
    - prometheus-client==0.7.1
    - prompt-toolkit==2.0.9
    - protobuf==3.8.0
    - psutil==5.6.3
    - ptyprocess==0.6.0
    - pyasn1==0.4.8
    - pyasn1-modules==0.2.8
    - pycparser==2.19
    - pycuda==2019.1.2
    - pygments==2.4.2
    - pyparsing==2.4.0
    - pyqt5==5.13.0
    - pyqt5-sip==4.19.18
    - pyrsistent==0.14.11
    - pyside2==5.13.0
    - python-dateutil==2.8.0
    - pytools==2020.1
    - pytz==2019.1
    - pywavelets==1.0.3
    - pyyaml==5.1.1
    - pyzmq==18.0.0
    - qdarkgraystyle==1.0.2
    - qdarkstyle==2.7
    - qtconsole==4.5.1
    - requests==2.22.0
    - requests-oauthlib==1.3.0
    - rsa==4.0
    - scikit-image==0.15.0
    - scikit-video==1.1.11
    - scipy==1.2.1
    - send2trash==1.5.0
    - shiboken2==5.13.0
    - six==1.12.0
    - tensorboard==1.15.0
    - tensorboard-plugin-wit==1.6.0.post3
    - tensorflow-estimator==1.15.1
    - tensorflow-gpu==1.15.0
    - termcolor==1.1.0
    - terminado==0.8.2
    - testpath==0.4.2
    - toolz==0.9.0
    - torch==1.1.0
    - torchdiffeq==0.0.1
    - torchvision==0.3.0
    - tornado==6.0.3
    - tqdm==4.32.1
    - traitlets==4.3.2
    - urllib3==1.25.3
    - wcwidth==0.1.7
    - webencodings==0.5.1
    - werkzeug==0.15.4
    - widgetsnbextension==3.4.2
    - wrapt==1.11.2
    - zipp==0.5.2

Answer 1

In the .yml file. For the packages that it didn't like. Replace the version number with the first value, like so

instead of:

• pytorch=1.1.0
• torchvision=0.2.2

use:

• pytorch=1
• torchvision=0

conda will figure it out.

Hope this helps.

Answer 2

Use Ubuntu 18.04 x86 (linux-64) and the environment.yml provided will work.

It fails on MacOS (M1 Silicon).

As has been pointed out in the other reply; exported environment files with explicit build numbers, and as it turns out fixed package version combinations; may not work if this host platform is different.

Exported environments are a great way to get reproducible environments, but the build platform must be the same. I suggest using conda info on the origin host and on the target host to check if they are the same.

Answer 3

Conda does not work well with large environments in which everything pinned to specific versions (in contrast to other ecosystems in which pinning everything is the standard). The result of conda env export, which is what this probably is, here also includes the build numbers, which are almost always too specific (and often platform-specific) for the purpose of installing the right version of the software. It's great for things like reproducibility of scientific work (specific versions and builds of everything need to be known), but not great for installing software (there is plenty of flexibility in versions that should work with any package).

I'd start by removing the build pins (dropping everything after the second = in each line) so that only the versions are pinned. After that, I'd start removing version pins.