Anaconda

Anaconda is a data science platform which includes Python and R.

Documentation

Usage

Multiple versions of Anaconda are available on Bridges.  In addition, environments tailored for AI applications which include Anaconda and other popular AI/Machine Learning/Big Data packages, such as TensorFlow, Theano, Keras, pandas, opencv, scikit-learn, and more are set up for you to use.  

 

General instructions

To see what versions of Anaconda are available, type

module avail anaconda

Note that anaconda2 modules use python2 and anaconda3 modules use python3.

To see what other modules are needed, what commands are available and how to get additional help type

module help anaconda-version

To use Anaconda, include a command like this in your batch script or interactive session to load the Anaconda module:

module load anaconda-version

Be sure you also load any other modules needed, as listed by the module help anaconda command.

 

 

Adding to an environment

If you need additional software, you can create a new environment and install it there.  Steps to do this are:

  1. Get an interactive session with the interact command. Use the egress option  so that you will be able to access the anaconda website.
  2. Load the anaconda module you want. Type module avail anaconda to see what versions are available.
  3. Use the conda create command to create your new environment.
  4. Activate your new environment.
  5. Install the software you need.

 This example session creates a new environment and installs fitsio.

[username@login006 ~]$ interact --egress

A command prompt will appear when your session begins
"Ctrl+d" or "exit" will end your session

srun: job 5897598 queued and waiting for resources
srun: job 5897598 has been allocated resources
[username@r003 ~]$ module load anaconda3
[username@r003 ~]$ conda create --name new-env
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.5.4
  latest version: 4.6.14

Please update conda by running

    $ conda update -n base conda



## Package Plan ##

  environment location: /home/username/.conda/envs/new-env


Proceed ([y]/n)? y

Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use:
# > source activate new-env
#
# To deactivate an active environment, use:
# > source deactivate
#

[username@r003 ~]$ source activate new-env
(new-env) [username@r003 ~]$ conda install -c conda-forge fitsio
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.5.4
  latest version: 4.6.14

Please update conda by running

    $ conda update -n base conda



## Package Plan ##

  environment location: /home/username/.conda/envs/new-env

  added / updated specs:
    - fitsio


The following packages will be downloaded:
(a list of packages to be downloaded and installed will be displayed)
.
.
.
Preparing transaction: done Verifying transaction: done Executing transaction: done (new-env) [username@r003 ~]$

At this point, a directory named ~/.conda/envs/new-env will have been created for you.  The /bin subdirectory  will contain your new binaries. 

 

 

PSC created environments for AI applications

We have built some environments that include software for AI, Big Data and machine learning applications.

The AI environments are built for Bridges' GPU nodes.  Be sure to use one of the GPU partitions.  See the Running jobs section of the Bridges User Guide for information on Bridges' partitions and how to choose one to use. 

Type

module avail AI/anaconda

to see the AI environments which you can use. 

For additional help, type

module help AI/anaconda-version

Note that AI/anaconda2 environments use python2, while AI/anaconda3 environments use python3

 

See what the PSC defined AI environment contains

To see the full list of software included in a given environment, first load the module and activate the environment with these commands:

module load AI/anaconda-version
source activate $AI_ENV

To see what is included in $AI_ENV, type 

conda list

 

Customize the PSC defined AI environment

If you need software that is not in the pre-built environment, you can create a new environment by cloning the PSC defined one and then customizing it. First load the module and activate the PSC defined environment, as above, then  clone it with

conda create --prefix  path-to-your-directory/your-new-environment-name --clone $AI_ENV

Then you can activate the new environment and proceed with your customization. See the example below for more detail.

 

Examples

Example sessions are shown below for common uses of anaconda.  

Use Tensorflow and python3

Use the following commands:

interact -gpu
module load AI/anaconda3-5.1.0_gpu
source activate $AI_ENV
python
import tensorflow

 

Use Tensorflow and python2

Use the following commands.

interact -gpu
module load AI/anaconda2-5.1.0_gpu
source activate $AI_ENV
python
import tensorflow

Customize the PSC defined environment

In this example, the user installs the h5py package in a new environment she is creating. Use the following commands.  Note:

The conda list command shows what packages are currently installed. Check to see if what you need is already available.  The conda list command shows the version number of the installed packages.

The conda create command clones $AI_ENV to create a new environment.  This can take a long time, so ask for an hour of time with the interact command. 

Here, the new environment is named clone-env-1, and is stored in the user's pylon5 home directory.  The --prefix flag names the full path to the where the environment will be stored. You can name the environment anything you like and store it in any directory you like.

interact -gpu --egress -t 01:00:00
module load AI/anaconda3-5.1.0_gpu
source activate $AI_ENV
conda list
conda create --prefix /pylon5/groupname/username/clone-env-1 --clone $AI_ENV
conda activate /pylon5/groupname/username/clone-env-1
conda install h5py

Conda install will install the newest version of the package. If you want to install a version of the package not available in the public installations use the --revision option to the conda install command.

 

Use the additional packages you installed in a subsequent session

You can use any additional packages you install in the same session in which you install them. To access them in subsequent sessions, follow these steps.  In this example, the user created the environment clone-env-1 and installed h5py in it in a previous session.

interact -gpu
module load AI/anaconda3-5.1.0_gpu
source activate /pylon5/groupname/username/clone-env-1

python
import h5py

 

User Information

Passwords
Connect to PSC systems:
Policies
Technical questions:

Send mail to remarks@psc.edu or call the PSC hotline: 412-268-6350.