Install MKL using conda on IBM Power 9 machine - anaconda

I cannot install mkl using conda on a IBM Power 9 machine. It seems that conda cannot find any suitable version for this machine since conda install mkl installs mkl on a RedHat machine without any error; though, on the IBM Power 9 with either conda install -c anaconda mkl or conda install mkl I get:
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:
- mkl
Current channels:
- https://conda.anaconda.org/anaconda/linux-ppc64le
- https://conda.anaconda.org/anaconda/noarch
- https://repo.anaconda.com/pkgs/main/linux-ppc64le
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/linux-ppc64le
- 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.
I also tried to download mkl from https://anaconda.org/anaconda/mkl/files and install it conda install on the machine, which was successfully installed. But, after that whenever I wanted to install a new package, I got an inconsistency error by conda:
Collecting package metadata (current_repodata.json): done
Solving environment: |
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- <unknown>/osx-64::mkl==2019.4=intel_233 failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: \
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- <unknown>/osx-64::mkl==2019.4=intel_233 failed with initial frozen solve. Retrying with flexible solve.
Solving environment: /
Found conflicts! Looking for incompatible packages. failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Package curl conflicts for:
cmake -> curl
anaconda==2019.07=py37_0 -> curl==7.65.2=hbc83047_0
pycurl -> curl=7.55
curl
Package libcurl conflicts for:
curl -> libcurl[version='7.59.0|7.60.0|7.61.0|7.61.1|7.62.0|7.63.0|7.63.0|7.64.0|7.64.1|7.65.2',build='h20c2e04_0|h20c2e04_0|h20c2e04_1000|h20c2e04_0|h20c2e04_0|h20c2e04_0|h1ad7b7a_0|h20c2e04_2']
cmake -> curl -> libcurl[version='7.59.0|7.60.0|7.61.0|7.61.1|7.62.0|7.63.0|7.63.0|7.64.0|7.64.1|7.65.2',build='h20c2e04_0|h20c2e04_0|h20c2e04_1000|h20c2e04_0|h20c2e04_0|h20c2e04_0|h1ad7b7a_0|h20c2e04_2']
anaconda==2019.07=py37_0 -> pycurl==7.43.0.3=py37h1ba5d50_0 -> libcurl[version='>=7.64.1,<8.0a0']
I appreciate any help or comment.

Related

Install a specific version of PyTorch on M1 chip arm64

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 .

Cannot install tensorflow-deps for Apple Silicon

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.

Conflicts during PyGMO installation on Mac OS X 11.2.2 with Anaconda

I am attempting to install PyGMO on Mac OS X 11.2.2 (with Anaconda which I reinstalled so the Anaconda Navigator is now upgraded to 2.0.1.)
After the installation starts, it collects package metadata and reports it found package conflicts. How can I solve the conflict so that I can run PyGMO?
Here is the start:
$ conda install -c conda-forge pygmo
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \
Found conflicts! Looking for incompatible packages.
After few hours, the Terminal returns a long report of conflicts and stops there. Here is a representative piece of output:
Package selectors2 conflicts for:
wurlitzer -> selectors2
spyder-kernels -> wurlitzer[version='>=1.0.3'] -> selectors2
Package mpmath conflicts for:
anaconda==2020.07=py38_0 -> sympy==1.6.1=py38_0 -> mpmath[version='>=0.19']
sympy -> mpmath[version='>=0.19']
anaconda==2020.07=py38_0 -> mpmath==1.1.0=py38_0
Package anyio conflicts for:
jupyterlab -> jupyter_server[version='>=1.4,<2'] -> anyio[version='>=2.0.2|>=2.0.2,<3']
jupyterlab_server -> jupyter_server[version='>=1.4,<2'] -> anyio[version='>=2.0.2|>=2.0.2,<3']
Package py-lief conflicts for:
conda-build -> py-lief
anaconda==2020.07=py38_0 -> py-lief==0.10.1=py38haf313ee_0
Note that strict channel priority may have removed packages required for satisfiability.
I followed the official installation guidelines and set the additional channel and its priority. I also checked this command but that is essentially the same thing. I also tried the installation commands from PyPI. And I tried this hint as well
There are two possible states:
Conda solver is correct. The previous package constraints you have in the environment are incompatible with installing pygmo. In that case, you either need to track down the conflicting constraints and try to manually loosen them (not recommended for Anaconda base), or you need to make a new environment:
conda create -n pygmo_env -c conda-forge pygmo
Include whatever other packages you need in there. E.g., ipykernel if you plan on using it as a Jupyter kernel.
Conda solver is bugging out. The solver is reporting trouble solving when it really shouldn't be. This happens, and especially happens when mixing channels (defaults and conda-forge). Many find Mamba, the drop-in replacement for Conda, to be more reliable (and definitely faster!).
conda install conda-forge::mamba
mamba install -c conda-forge pygmo
Unfortunately, it's hard to tell which state it's in. Many of us have been down the rabbit hole of trying to sort through the constraint reports and sometimes there really isn't a sensible conflict to be found. For practical purposes, I'd recommend trying out mamba. If it also fails, then at least you'll have good evidence that you're in state (1).
Additional Commentary
Despite upbeat documentation about installing from any channel in Anaconda Cloud, an Anaconda distribution is highly constrained - i.e., has too many packages - and only tests for co-installation of packages from the defaults channel. Additionally, Conda Forge and Anaconda have different build stacks, so there can be runtime package incompatibilities even when the solver allows co-installation.
Generally, I'd recommend making liberal use of environment creation. Aim to have separate environments for separate tasks/projects. If you plan on frequently using more than a vanilla Anaconda distribution, consider Miniforge or one of its variants. One can always create an Anaconda environment with conda create -n foo -c defaults anaconda.

How to resolve inconsistent environment - Jupyter Lab

I tried to install graphviz but got a message that my environment is inconsistent. Looking at other posts I tried
conda install anaconda
conda install -c anaconda anconda
conda update --all
conda uninstall anaconda
but all failed.
When running "conda update --all", although it looks as if it fixed the problem, running the same command again gives the same output.
When running 'conda install anaconda' it ran for 6 hours without doing much. Eventually I stopped it. Here is the screen output:
(base) C:\Windows\system32>conda install anaconda
Collecting package metadata (current_repodata.json): done
Solving environment: |
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- defaults/win-64::ipykernel==5.3.4=py38h5ca1d4c_0
- conda-forge/noarch::ipympl==0.6.3=pyhd8ed1ab_0
- defaults/noarch::ipywidgets==7.6.3=pyhd3eb1b0_1
- conda-forge/noarch::nbclassic==0.2.5=pyhd8ed1ab_0
- defaults/noarch::nbclient==0.5.1=py_0
- defaults/win-64::nbconvert==6.0.7=py38_0
- defaults/win-64::notebook==6.1.4=py38_0
- defaults/win-64::widgetsnbextension==3.5.1=py38_0
- defaults/win-64::_ipyw_jlab_nb_ext_conf==0.1.0=py38_0
failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry
with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: \
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- defaults/win-64::ipykernel==5.3.4=py38h5ca1d4c_0
- conda-forge/noarch::ipympl==0.6.3=pyhd8ed1ab_0
- defaults/noarch::ipywidgets==7.6.3=pyhd3eb1b0_1
- conda-forge/noarch::nbclassic==0.2.5=pyhd8ed1ab_0
- defaults/noarch::nbclient==0.5.1=py_0
- defaults/win-64::nbconvert==6.0.7=py38_0
- defaults/win-64::notebook==6.1.4=py38_0
- defaults/win-64::widgetsnbextension==3.5.1=py38_0
- defaults/win-64::_ipyw_jlab_nb_ext_conf==0.1.0=py38_0
failed with initial frozen solve. Retrying with flexible solve.
Solving environment: /
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
Examining clyent: 23%|█████? | 41/176 [00:28<01:33, 1.44it/s]/
Examining libsodium: 38%|███████▌ | 67/176 [01:12<03:33, 1.96s/it]|
Examining conda-env: 41%|████████? | 72/176 [01:13<01:42, 1.02it/s]\
Examining m2w64-gmp: 56%|███████████? | 99/176 [03:40<03:11, 2.49s/it]\
Examining mkl-service: 65%|███████████ | 114/176 [04:38<06:29, 6.28s/it]\
Examining chardet: 69%|██████████████? | 121/176 [04:40<01:08, 1.24s/it]/
Examining conflict for six htmlmin testpath ipython console_shortcut wcwidth cf\
Examining conflict for six htmlmin testpath ipython console_shortcut wcwidth cf-
failed -
CondaError: KeyboardInterrupt
Terminate batch job (Y/N)? y
(base) C:\Windows\system32>

conda create: UnsatisfiableError

I am trying to create an environment for an installation (https://github.com/linzhi2013/MitoZ/), but I get the following error. Any suggestions what I need to install/uninstall to make it work?
:~$ conda create -n mitozEnv libgd=2.2.4 python=3.6.0 biopython=1.69 ete3=3.0.0b35 perl-list-moreutils perl-params-validate perl-clone circos=0.69 perl-bioperl blast=2.2.31 hmmer=3.1b2 bwa=0.7.12 samtools=1.3.1 infernal=1.1.1 tbl2asn openjdk
Collecting package metadata (current_repodata.json): done
Solving environment: failed
Collecting package metadata (repodata.json): done
Solving environment: failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
- biopython=1.69 -> reportlab -> pillow[version='>=2.4.0'] -> tk[version='>=8.6.9,<8.7.0a0']
- blast=2.2.31 -> boost=1.60 -> python=3.5 -> tk[version='>=8.6.8,<8.7.0a0']
- ete3=3.0.0b35 -> lxml -> python[version='>=3.6,<3.7.0a0'] -> tk[version='>=8.6.9,<8.7.0a0']
- python=3.6.0 -> tk=8.5
Take it one step at a time.
Why are you specifying a fixlevel 3.6.0 for Python? Unless you have a very good reason, relax this to python=3.6. Newer fixlevels might work with different versions of tk, which could resolve some of your problems.
blast 2.2.31 drags in a dependency on Python 3.5 via boost 1.60. Relax the version of blast, so you can pull in a version of boost that works with the Python 3.6 you want.
With those changes, try again and see what problems remain.

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