I tried to install dgl(https://github.com/dmlc/dgl)
There were several ways to install it.(https://docs.dgl.ai/install/index.html#install-from-source)
pip
conda
from git source
from whl
and I failed with error message when I tried pip
$ pip install dgl-cu101
ERROR: Could not find a version that satisfies the requirement dgl-cu101 (from versions: none)
ERROR: No matching distribution found for dgl-cu101
even pip search spot the package
$ pip search dgl
dgl (0.4.1) - Deep Graph Library
dgl-bots.py (1.1.0) - A python wrapper for https://bots.discord.gl
dgl-cu100 (0.4.1) - Deep Graph Library
dgl-cu92 (0.4.1) - Deep Graph Library
dgl-cu90 (0.4.1) - Deep Graph Library
dgl-cu101 (0.4.1) - Deep Graph Library
dgl-cu102 (0.5a200108) - Deep Graph Library
conda also does not work
$ conda install -c dglteam dgl-cuda10.1
Solving environment: failed
PackagesNotFoundError:
The following packages are not available from current channels:
- dgl-cuda10.1
Current channels:
- https://conda.anaconda.org/dglteam/linux-ppc64le
- https://conda.anaconda.org/dglteam/noarch
- https://repo.anaconda.com/pkgs/main/linux-ppc64le
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/free/linux-ppc64le
- https://repo.anaconda.com/pkgs/free/noarch
- https://repo.anaconda.com/pkgs/r/linux-ppc64le
- https://repo.anaconda.com/pkgs/r/noarch
- https://repo.anaconda.com/pkgs/pro/linux-ppc64le
- https://repo.anaconda.com/pkgs/pro/noarch
- https://conda.anaconda.org/conda-forge/linux-ppc64le
- https://conda.anaconda.org/conda-forge/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.
install with source code is not available option because I am the remote client to the server and has no root access
install with whl seems nice but also occurred error.(https://pypi.org/project/dgl/#files)
$ pip install dgl_cu101-0.4.1-cp37-cp37m-manylinux1_x86_64.whl
ERROR: dgl_cu101-0.4.1-cp37-cp37m-manylinux1_x86_64.whl is not a supported wheel on this platform.
I read almost every articles and most of them said it would be the environment problem,
but as far as I know, they match!
My env server
CentOS 7
python 3.7
64 bit
minsky
4 GPUs
designed for ML
My env client
macos
iterm2
no root access
access from different city
How can I solve this problem?
Please help.
Your conda channel
https://conda.anaconda.org/dglteam/linux-ppc64le
gives the clue. Your system seems to be based on a ppc64le CPU, not the most frequently seen x86_64.
As you can see On the conda page, only linux-64 (i.e. x86_64) is available. Same goes for the pypi project.
So your setup does not match.
install with source code is not available option because I am the remote client to the server and has no root access
You should not need root access to compile the source code. The requirements listed in the guide are
gcc-c++ python3-devel make cmake
which, if not available yet could be installed using conda:
conda install -c conda-forge make cmake libgcc
Related
I would like to install torch==1.0.0 and torchvision==0.2.1 on my Mac macOS-12.5.1-arm64-arm-64bit in a conda environment (python 3.9).
I referred to the PyTorch documentation: https://pytorch.org/get-started/previous-versions/#v100
using pip :
(first) user#Users-MacBook-Air first-order-model % pip install torch==1.0.0 torchvision==0.2.1
ERROR: Could not find a version that met the torch==1.0.0 requirement (from versions: 1.9.0, 1.10.0, 1.10.1, 1.10.2, 1.11.0, 1.12.0, 1.12.1)
ERROR: No matching distribution found for torch==1.0.0
or conda :
(first) user#Users-MacBook-Air first-order-model % conda install pytorch==1.0.0 torchvision==0.2.1 -c pytorch
Collect the package metadata (current_repodata.json): done
Resolution environment: failed with initial resolution frozen. Retry with a flexible solution.
Collect package metadata (repodata.json): done
Resolution environment: initial frozen resolution failed. Retry with a flexible solution.
PackagesNotFoundError: The following packages are not available in the current channels:
- pytorch==1.0.0
Current channels:
- https://conda.anaconda.org/pytorch/osx-arm64
- https://conda.anaconda.org/pytorch/noarch
- https://repo.anaconda.com/pkgs/main/osx-arm64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/osx-arm64
- https://repo.anaconda.com/pkgs/r/noarch
To search for other channels that may provide the conda package you are looking for, go to
you are looking for, go to
https://anaconda.org
and use the search bar at the top of the page.
Do you know if this is possible? I don't think I've seen these versions available for arm64 here https://anaconda.org/soumith/pytorch/files .
I'm trying to set-up by Apple Silicon Mac to be able to train tf models using its GPU.
I tried following the official instructions but I am getting the following error:
>>> conda install -c apple tensorflow-deps
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- tensorflow-deps
Current channels:
- https://conda.anaconda.org/apple/osx-64
- https://conda.anaconda.org/apple/noarch
- https://repo.anaconda.com/pkgs/main/osx-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/osx-64
- https://repo.anaconda.com/pkgs/r/noarch
- https://conda.anaconda.org/conda-forge/osx-64
- https://conda.anaconda.org/conda-forge/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.
Not sure if it should matter but I didn't install Miniforge because I already have Anaconda installed comprehensively. Surely, this can't be the reason? (I didn't want to install Miniforge not to mess up my env by having multiple Conda installations).
I did add the "apple" channel in the Navigator manually and the package does seem to be there:
https://anaconda.org/apple/tensorflow-deps
What am I missing here?
I also struggled with this for a while. The only way I was able to get a successful environment set up was indeed installing conda through mini forge. Based on this link I believe this is because of the other packages Anaconda pre-installs that are not ARM compatible.
I followed this thread to remove my Anaconda installation. Once that is done the instructions you linked should be successful.
I am attempting to install CERNS ROOT in anaconda, for use of pyRoot. (I am using conda 4.10.3)
I have set up a new environment with python 2.7, because I believe I read somewhere that ROOT does not work well with python 3. After installing python to the new environment and activating it, I have added conda-forge to the current channels and attempted to install the following:
https://anaconda.org/conda-forge/root-dependencies
Using:
conda install -c conda-forge root-dependencies
This however returned the following:
(pyRoot) C:\Users\George>conda install -c conda-forge root-dependencies
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- root-dependencies
Current channels:
- https://conda.anaconda.org/conda-forge/win-64
- https://conda.anaconda.org/conda-forge/noarch
- https://repo.anaconda.com/pkgs/main/win-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/free/win-64
- https://repo.anaconda.com/pkgs/free/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.
I am not sure why this is not working, as I am fairly sure the root-dependencies are available on the conda-forge channel as per the link.
I have tried the following:
SET CONDA_RESTORE_FREE_CHANNEL=1
Just in case it was part of the free channel that may have been dropped, but I still get the same error.
Any ideas are appreciated :)
The package is not built for win-64 platform, which is what OP channel configuration indicates is being used. Consider WSL2 or Docker (ROOT Project provides pre-built images).
If you would like Conda Forge to build a Windows version, submit an Issue on the feedstock. Just be aware that ROOT Project itself only has beta support for Windows natively, so it's likely not a trivial task.
I have installed bioconda following the instructions at https://bioconda.github.io/user/install.html#set-up-channels. Then I tried
conda install bwa
conda install bcftools
conda install plink2
They all installed fine. However, when I tried
conda install bcftools-gtc2vcf-plugin
or
conda install -c bioconda bcftools-gtc2vcf-plugin
as instructed at https://bioconda.github.io/recipes/bcftools-gtc2vcf-plugin/README.html, I got errors as follows:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- bcftools-gtc2vcf-plugin
Current channels:
- https://conda.anaconda.org/bioconda/osx-64
- https://conda.anaconda.org/bioconda/noarch
- https://conda.anaconda.org/conda-forge/osx-64
- https://conda.anaconda.org/conda-forge/noarch
- https://repo.anaconda.com/pkgs/main/osx-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/osx-64
- https://repo.anaconda.com/pkgs/r/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.
Any help would be highly appreciated.
Thanks in advance!
I would advise (as of 2020-01-06) not to use the bcftools-gtc2vcf-plugin as it is an old version missing many features compared to the current version. I would advise either to compile from source (https://github.com/freeseek/gtc2vcf) or alternatively to download pre-compiled binaries (https://personal.broadinstitute.org/giulio/gtc2vcf) that should work on systems with ≥GLIBC_2.3 installed (and making sure you are running the latest version of BCFtools)
If you get the error:
No functional bcftools plugins were found in
BCFTOOLS_PLUGINS="/Users/moxu/xbin/seq/bcftools/plugins".
- Is the plugin path correct?
- Run "bcftools plugin -lv" for more detailed error output.
Could not load "gtc2vcf".
(a bcftools plugin bug that the maintainers will fix soon), can you try to run one of the following commands instead:
$ bcftools plugin gtc2vcf -vv
$ bcftools +gtc2vcf -vv
$ bcftools plugin /Users/moxu/xbin/seq/bcftools/plugins/gtc2vcf.so -vv
$ bcftools +/Users/moxu/xbin/seq/bcftools/plugins/gtc2vcf.so -vv
You should get a reason for why the plugin is not loading. A typical error message could look like this:
/Users/moxu/xbin/seq/bcftools/plugins/gtc2vcf.so:
dlopen .. /lib64/libc.so.6: version `GLIBC_2.3' not found (required by /Users/moxu/xbin/seq/bcftools/plugins/gtc2vcf.so)
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