PackageNotFoundError: cudnn while passing the arguments in a text file - anaconda

I am running the following command -
conda install -y --file b.txt -p <env_path>
Contents of b.txt -
cudnn=6.0.0
I get the following error -
Fetching package metadata .............
PackageNotFoundError: Packages missing in current channels:
- cudnn 6.0.0
We have searched for the packages in the following channels:
- https://repo.continuum.io/pkgs/main/linux-64
- https://repo.continuum.io/pkgs/main/noarch
- https://repo.continuum.io/pkgs/free/linux-64
- https://repo.continuum.io/pkgs/free/noarch
- https://repo.continuum.io/pkgs/r/linux-64
- https://repo.continuum.io/pkgs/r/noarch
- https://repo.continuum.io/pkgs/pro/linux-64
- https://repo.continuum.io/pkgs/pro/noarch
- https://conda.anaconda.org/conda-forge/linux-64
- https://conda.anaconda.org/conda-forge/noarch
cudnn is part of anaconda channel.
However, when I run this, things work fine and cudnn is installed -
conda install -y cudnn=6.0.0 -p <env_path>
Any pointers on why passing it via file is not working?

changing cudnn-6.0.0 to cudnn-6.0-0 worked!

Related

Weird error in creating conda environment from yml file? (PackagesNotFoundError for the yml file itself)

I'm reinstalling Conda after a PC factory reset and trying to re-create an old conda environment from a yml file that I created by
conda env export --prefix $path_to_old_env_dir > voice_dep.yml
The resulting yml file looks ok to me, here's what it looks like:
name: voiceeda
channels:
- defaults
- conda-forge
dependencies:
- ca-certificates=2022.12.7=h5b45459_0
- libsqlite=3.40.0=hcfcfb64_0
- openssl=1.1.1s=hcfcfb64_1
- pip=22.3.1=pyhd8ed1ab_0
- python=3.9.13=h6244533_2
- setuptools=66.1.1=pyhd8ed1ab_0
- sqlite=3.40.0=hcfcfb64_0
- tzdata=2022g=h191b570_0
- ucrt=10.0.22621.0=h57928b3_0
- vc=14.3=hb6edc58_10
- vs2015_runtime=14.34.31931=h4c5c07a_10
- wheel=0.38.4=pyhd8ed1ab_0
- pip:
- anyio==3.6.2
- argon2-cffi==21.3.0
- argon2-cffi-bindings==21.2.0
- arrow==1.2.3
...
but when I try to run
conda create -n voiceeda -f voice_dep.yml
The following odd error occurs.
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
- voice_dep.yml
I'd understand if it wasn't finding a particular package, I can remove versions etc. if so, but why is it saying it can't find the yml file itself? I'm very confused, wondering if I missed a crucial setup step during conda installation or smth? I'm on Windows 10, and installed anaconda to a D drive (conda version 23.1.0 & Python 3.9.13.).
Any help would be much appreciated, thank you!

setting up Kallisto software [duplicate]

I am trying to install some packages from the Bioconda channel with Conda but even though the channel is added, I get to following error:
C:\Users\matti>conda install -c bioconda pybedtools
Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
- pybedtools
Current channels:
- https://conda.anaconda.org/bioconda/win-64
- https://conda.anaconda.org/bioconda/noarch
- https://conda.anaconda.org/conda-forge/win-64
- https://conda.anaconda.org/conda-forge/noarch
- https://repo.continuum.io/pkgs/main/win-64
- https://repo.continuum.io/pkgs/main/noarch
- https://repo.continuum.io/pkgs/free/win-64
- https://repo.continuum.io/pkgs/free/noarch
- https://repo.continuum.io/pkgs/r/win-64
- https://repo.continuum.io/pkgs/r/noarch
- https://repo.continuum.io/pkgs/pro/win-64
- https://repo.continuum.io/pkgs/pro/noarch
- https://repo.continuum.io/pkgs/msys2/win-64
- https://repo.continuum.io/pkgs/msys2/noarch
- https://conda.anaconda.org/daler/win-64
- https://conda.anaconda.org/daler/noarch
- https://conda.anaconda.org/anaconda-fusion/win-64
- https://conda.anaconda.org/anaconda-fusion/noarch
This also happens for other Bioconda packages like bowtie2. I have tried regular pip install and easy_install but those do not work either. Any ideas?
Additional Info
OS: Windows
Anaconda base
From your command line it appears you are on windows. There are several veresions of pybedtools on bioconda, however, if I grep through them, they are all for the linux platform.
If you're on Windows 10, you could consider setting up the 'windows subsystem for linux' (and possibly Xming), installing conda, and then installing pybedtools. This is obviously a long-winded approach, but would open up many bioconda packages to you

conda: why I can not install pkgs in one environment, while I can install in another?

I'm using two environment of conda. I can not intall packages in one env, while I can intall packages in the other environment.
The error massage is: 'solving environment: failed'
system: windows 10 x64
The error msg:
(py3env) C:\>conda install cython
Collecting package metadata (current_repodata.json): done
Solving environment: failed
Collecting package metadata (repodata.json): done
Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
- anaconda/pkgs/free/win-64::protobuf==3.2.0=py36_0 -> libprotobuf==3.2.0
- anaconda/pkgs/free/win-64::tensorflow==1.2.1=py36_0 -> backports.weakref==1.0rc1
- anaconda/pkgs/free/win-64::tensorflow==1.2.1=py36_0 -> bleach==1.5.0
- anaconda/pkgs/free/win-64::tensorflow==1.2.1=py36_0 -> html5lib==0.9999999
Current channels:
- https://repo.anaconda.com/pkgs/main/win-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/win-64
- https://repo.anaconda.com/pkgs/r/noarch
- https://repo.anaconda.com/pkgs/msys2/win-64
- https://repo.anaconda.com/pkgs/msys2/noarch
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
While the success info in another environment:
(py2env) C:\>conda install cython Collecting package metadata (current_repodata.json): done Solving environment: done
## Package Plan ##
environment location: C:\Users\sonic\Anaconda3\envs\py2env
added / updated specs:
- cython
The following packages will be downloaded:
package | build
---------------------------|-----------------
certifi-2019.6.16 | py27_0 151 KB
cython-0.29.11 | py27hc56fc5f_0 2.0 MB
------------------------------------------------------------
Total: 2.1 MB
The following NEW packages will be INSTALLED:
cython pkgs/main/win-64::cython-0.29.11-py27hc56fc5f_0
The following packages will be UPDATED:
certifi anaconda/pkgs/free::certifi-2016.2.28~ --> pkgs/main::certifi-2019.6.16-py27_0
Proceed ([y]/n)?
I think it is because you have packages installed from the "free" channel, but that channel has been removed. So conda is confused about what to do. You should read the blog post anaconda.com/why-we-removed-the-free-channel-in-conda-4-7 and temporarily add the "free" channel back to your configuration as described in that blog by running the command conda config --set restore_free_channel true. After you run that command, you can set the restore free channel back to false if you finished installing the Cython. Thanks for the comments of #darthbith

How to separate packages with multiple channels in yaml using conda to create customized env

I need to create an environment mock up the one using virtualenv, the packages belong to various channels in anaconda. Though I specified channels, I received error for some packages.
my_env.yml:
name: my_env
channels:
- anaconda
- conda-forge
dependencies:
- numpy=1.15.2
- scipy=1.1.0
- scikit-learn=0.20.0
- pandas=0.22.0
- SQLAlchemy=1.1.14
- graphviz=0.8
- slacker=0.9.60
Note:
slacker is in conda-forge channel
SQLAlchemy and graphviz are in anaconda channel
the others are just in regular (default) channel
When I run the command:
conda env create -f /home/my_env.yml
I received the following error:
Solving environment: failed
ResolvePackageNotFound:
- sqlalchemy=1.1.14
- graphviz=0.8
Seems channel anaconda is NOT picked up?
How can I fix this yml file?
Thank you very much.
This is not an answer because the way you have it worked for me with the dependencies I rely on. Did you try including defaults as well as the channels you specify?
Here's my YAML file ...
name: talia36
channels:
- defaults
- pytorch
dependencies:
- coverage
- cudatoolkit==10.0.130
- dataclasses
- future
- joblib
- jupyter
- keyring
- matplotlib
- mypy
- numpy
- pandas==0.25.3
- param
- pip
- pylint
- python==3.6.10
- python-dateutil
- pytorch==1.2.0
- pyyaml
- scikit-learn
- scipy
- seaborn
- sqlite
- tensorboard==1.14.0
- torchvision==0.4.0
- pip:
- --requirement experiment-requirements.txt

Installing older version of h2o in conda virtual environment on Windows

I'm struggling to figure out conda virtual environments on windows. All I want is to be able to have different versions of h2o installed at the same time because of their insane decision to not allow you to be able to load files saved in even the most minor different version.
I created a virtual environment by cloning my base anaconda:
conda create -n h203_14_0_7 --clone base
I then activated the virtual environment like so:
C:\ProgramData\Anaconda3\Scripts\activate h203_14_0_7
Now that I'm in the virtual environment (I see the (h203_14_0_7) at the beginning of the prompt), i want to uninstall the version of h2o in this virtual environment so I tried:
pip uninstall h2o
But this output
which to me looks like it's going to uninstall the global h2o rather than the virtual environment h2o. So I think it's using the global pip instead of the pip it should have cloned off the base. So how to I use the virtual environment pip to uninstall h2o just for my virtual environment and how can I be sure that it's doing the right thing?
I then ran
conda intall pip
and it seems that after that I was able to use pip to uninstall h2o only from the virtual environment (I hope). I then downloaded the older h2o version from here: https://github.com/h2oai/h2o-3/releases/tag/jenkins-rel-weierstrass-7
but when I try install it I get
(h203_14_0_7) C:\ProgramData\Anaconda3\envs\h203_14_0_7>pip install C:\Users\dan25\Downloads\h2o-3-jenkins-rel-weierstrass-7.tar.gz
Processing c:\users\dan25\downloads\h2o-3-jenkins-rel-weierstrass-7.tar.gz
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\ProgramData\Anaconda3\envs\h203_14_0_7\lib\tokenize.py", line 452, in open
buffer = _builtin_open(filename, 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\dan25\\AppData\\Local\\Temp\\pip-sf7r_6pm-build\\setup.py'
So what now?
I had trouble (e.g. https://0xdata.atlassian.net/browse/PUBDEV-3370 ) getting that approach to ever work. It felt like some kind of global dependency was in there, somewhere.
So, I personally just uninstall, and install the desired version, as I need to move between versions. (Actually, I am more likely to use a different VirtualBox or AWS image for each.)
However I noticed searching for conda on the H2O jira that there is a lot of activity recently. They might all be pointing out the same bug you have found, but if so it sounds like it is something getting enough attention to get fixed.
Aside: finding old versions (and your edit showing install problems)
To find, e.g. 3.14.0.7, google it with "h2o". The top hit is http://h2o-release.s3.amazonaws.com/h2o/rel-weierstrass/7/index.html
The "rel-weierstrass" represents 3.14.0, and the 7 is in the URL. (I've yet to see a full list of all the rel-XXX names, but google will always find at least one in the series, even if it won't find the exact minor version.)
Download the zip file you find there. Inside you will find both an R package, and a whl package for Python. So unzip it, extract the one you want, then pip install it.
These zip files are always on S3 (AFAIK). The link you showed was a source snapshot, on github.
Install requirements:
pip install requests tabulate numpy scikit-learn
Extract the archive:
zcat h2o-3-jenkins-rel-weierstrass-7.tar.gz | tar xvf -
cd into Python directory and build:
cd h2o-py
../gradlew build
I have this working now. I think the trick is to make sure you do NOT have h2o installed on your base python. I did the following:
pip uninstall h2o
conda create --name h2o-base pip
conda activate h2o-base
conda install numpy
conda install pandas
conda install requests
conda install tabulate
conda install colorama
conda install future
conda install jupyter
python -m pip install ipykernel
conda deactivate
And now to install specific versions of h2o, you need to URL of the .whl file for that version and you can find a list of the URLs of all the old versions here: https://github.com/h2oai/h2o-3/blob/master/Changes.md
So for example to install version 3.18.0.8:
conda create --name h2o-3-18-0-8 --clone h2o-base
conda activate h2o-3-18-0-8
pip install http://h2o-release.s3.amazonaws.com/h2o/rel-wolpert/8/Python/h2o-3.18.0.8-py2.py3-none-any.whl
python -m ipykernel install --user --name h2o-3-18-0-8 --display-name "Python (h2o-3-18-0-8)"
or version 3.20.0.2 (make sure to conda deactivate first):
conda create --name h2o-3-20-0-2 --clone h2o-base
conda activate h2o-3-20-0-2
pip install http://h2o-release.s3.amazonaws.com/h2o/rel-wright/2/Python/h2o-3.20.0.2-py2.py3-none-any.whl
python -m ipykernel install --user --name h2o-3-20-0-2 --display-name "Python (h2o-3-20-0-2)"
This set-up allows me to have multiple versions of h2o installed on the same computer and if I have to use serialized models I just have to run python from the virtual environment with the correct version of h2o installed. I think this is preferable to uninstalling and reinstalling h2o each time.
Here is the environments.yml file if you want to skip all the manual installs above:
name: h2o-base
channels:
- conda-forge
- defaults
dependencies:
- asn1crypto=0.24.0=py37_1003
- backcall=0.1.0=py_0
- bleach=3.0.2=py_0
- ca-certificates=2018.10.15=ha4d7672_0
- certifi=2018.10.15=py37_1000
- cffi=1.11.5=py37hfa6e2cd_1001
- chardet=3.0.4=py37_1003
- colorama=0.4.0=py_0
- cryptography=2.3=py37h74b6da3_0
- cryptography-vectors=2.3.1=py37_1000
- decorator=4.3.0=py_0
- entrypoints=0.2.3=py37_1002
- future=0.16.0=py37_1002
- icu=58.2=vc14_0
- idna=2.7=py37_1002
- ipykernel=5.1.0=pyh24bf2e0_0
- ipython=7.0.1=py37h39e3cac_1000
- ipython_genutils=0.2.0=py_1
- ipywidgets=7.4.2=py_0
- jedi=0.13.1=py37_1000
- jinja2=2.10=py_1
- jpeg=9b=vc14_2
- jsonschema=2.6.0=py37_1002
- jupyter=1.0.0=py_1
- jupyter_client=5.2.3=py_1
- jupyter_console=6.0.0=py_0
- jupyter_core=4.4.0=py_0
- libflang=5.0.0=vc14_20180208
- libpng=1.6.34=vc14_0
- libsodium=1.0.16=vc14_0
- llvm-meta=5.0.0=0
- markupsafe=1.0=py37hfa6e2cd_1001
- mistune=0.8.4=py37hfa6e2cd_1000
- nbconvert=5.3.1=py_1
- nbformat=4.4.0=py_1
- notebook=5.7.0=py37_1000
- openblas=0.2.20=vc14_8
- openmp=5.0.0=vc14_1
- openssl=1.0.2p=hfa6e2cd_1001
- pandas=0.23.4=py37h830ac7b_1000
- pandoc=2.3.1=0
- pandocfilters=1.4.2=py_1
- parso=0.3.1=py_0
- pickleshare=0.7.5=py37_1000
- pip=18.1=py37_1000
- prometheus_client=0.4.2=py_0
- prompt_toolkit=2.0.6=py_0
- pycparser=2.19=py_0
- pygments=2.2.0=py_1
- pyopenssl=18.0.0=py37_1000
- pyqt=5.6.0=py37h764d66f_7
- pysocks=1.6.8=py37_1002
- python=3.7.0=hc182675_1005
- python-dateutil=2.7.3=py_0
- pytz=2018.5=py_0
- pywinpty=0.5.4=py37_1002
- pyzmq=17.1.2=py37hf576995_1001
- qt=5.6.2=vc14_1
- qtconsole=4.4.2=py_1
- requests=2.19.1=py37_1001
- send2trash=1.5.0=py_0
- setuptools=40.4.3=py37_0
- simplegeneric=0.8.1=py_1
- sip=4.18.1=py37h6538335_0
- six=1.11.0=py37_1001
- tabulate=0.8.2=py_0
- terminado=0.8.1=py37_1001
- testpath=0.4.2=py37_1000
- tornado=5.1.1=py37hfa6e2cd_1000
- traitlets=4.3.2=py37_1000
- urllib3=1.23=py37_1001
- vc=14=0
- vs2015_runtime=14.0.25420=0
- wcwidth=0.1.7=py_1
- webencodings=0.5.1=py_1
- wheel=0.32.1=py37_0
- widgetsnbextension=3.4.2=py37_1000
- win_inet_pton=1.0.1=py37_1002
- wincertstore=0.2=py37_1002
- winpty=0.4.3=4
- zeromq=4.2.5=vc14_2
- zlib=1.2.11=vc14_0
- blas=1.0=mkl
- icc_rt=2017.0.4=h97af966_0
- intel-openmp=2019.0=118
- m2w64-gcc-libgfortran=5.3.0=6
- m2w64-gcc-libs=5.3.0=7
- m2w64-gcc-libs-core=5.3.0=7
- m2w64-gmp=6.1.0=2
- m2w64-libwinpthread-git=5.0.0.4634.697f757=2
- mkl=2019.0=118
- mkl_fft=1.0.6=py37hdbbee80_0
- mkl_random=1.0.1=py37h77b88f5_1
- msys2-conda-epoch=20160418=1
- numpy=1.15.2=py37ha559c80_0
- numpy-base=1.15.2=py37h8128ebf_0

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