Anaconda Environment
Background
Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing. The big difference between Conda and the pip package manager is in how the package dependencies are managed, which is a significant challenge for Python data science and the reason Conda exists.
(see webpage https://www.anaconda.com for details)
Existing Anaconda Environment
There are currently 6 Conda environments supported on HAL system
| Environment Name | Location | Description |
|---|---|---|
| base | /opt/apps/anaconda3 | Default Conda env with basic python packages, python version 3.7. |
deepspeed-v0.3.16 | ||
fastai-v0.1.18 | ||
| wmlce-v1.6.2 | /opt/apps/anaconda3/envs/wmlce-v1.6.1-py2.7 | IBM WMLCE-v1.6.2 (former PowerAI) package, python version 2.7. |
| wmlce-v1.7.0 | /opt/apps/anaconda3/envs/wmlce-v1.7.0-py3.7 | IBM WMLCE-v1.7.0 (former PowerAI) package, python version 3.7. |
| opence-v1.0.0 | ||
| opence-v1.1.2 | ||
| opence-v1.2.2 | ||
| opence-v1.3.1 | ||
| rapids |
Create a New Env from Existing Envs
We recommend our users to create a new environment from one of our existing powerai or wmlce environment.
conda create --name=<new_env> --clone=wmlce-v1.6.1-py3.6
The new Conda environment will be located within $HOME/.conda/envs/<new_env>, then users can search and/or install python packages via Conda
conda search r-tensorflow
conda install r-tensorflow
Create Anaconda Environment from Scratch
Users can also create a new environment from scratch
conda create --name=<new_env_name>
Important Note about Install package with pip
Some packages only support installing with "pip" and we allow users to install the package with "pip" within their own conda environment. However, install with "pip" is not always work since it could have a conflict with the Conda environment.