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- How to install a specific package?
- Users can not and should not install packages in existing python environments such as opence-v1.5.1.
- Users need to create their own python environment to install their own packages.
- Create a New Env from Existing Environment.
Create Conda Environment from Scratch.
- Users should search for all the available packages before installation.
Search Packages in All Default Channels.
Search Packages in a Specific Channel.
Code Block |
conda search openblas
- How to solve dependency conflict?
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Environment Name | Location | Description |
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base | /opt/apps/anaconda3 | Default Conda env with basic python packages. |
deepspeed-v0.3.16 | /opt/miniconda3/envs/deepspeed-v0.3.16 | DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. |
fastai-v0.1.18 | /opt/miniconda3/envs/fastai-v0.1.18 | fastai is a deep learning library that provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains and provides researchers with low-level components that can be mixed and matched to build new approaches. |
wmlce-v1.6.2 | /opt/anaconda3/envs/wmlce-v1.6.2 | Watson Machine Learning Community Edition is an IBM Cognitive Systems offering that is designed for the rapidly growing and quickly evolving AI category of deep learning. |
wmlce-v1.7.0 | /opt/anaconda3/envs/wmlce-v1.7.0 | Watson Machine Learning Community Edition is an IBM Cognitive Systems offering that is designed for the rapidly growing and quickly evolving AI category of deep learning. |
opence-v1.0.0 | /opt/miniconda3/envs/opence-v1.0.0 | Open-CE is a community-driven software distribution for machine learning that runs on standard Linux platforms with NVIDIA GPU technologies. |
opence-v1.1.2 | /opt/miniconda3/envs/opence-v1.1.2 | Open-CE is a community-driven software distribution for machine learning that runs on standard Linux platforms with NVIDIA GPU technologies. |
opence-v1.2.2 | /opt/miniconda3/envs/opence-v1.2.2 | Open-CE is a community-driven software distribution for machine learning that runs on standard Linux platforms with NVIDIA GPU technologies. |
opence-v1.3.1 | /opt/miniconda3/envs/opence-v1.3.1 | Open-CE is a community-driven software distribution for machine learning that runs on standard Linux platforms with NVIDIA GPU technologies. |
rapids | /opt/miniconda3/envs/rapids | The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. |
Create a New Env from Existing
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Environments
We recommend our users to create a new environment from one of our existing opence environment.
Code Block |
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language | bash |
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title | Create a New Env from Existing Env |
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conda create --name=<new_env> --clone=opence-v1.35.1 |
The new Conda environment will be located within $HOME/.conda/envs/<new_env>, then users can search and/or install python packages via Conda
Code Block |
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language | bash |
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title | Example: Search for a New Package |
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conda search r-tensorflow |
Create Conda Environment from Scratch
Users can also create a new environment from scratch
Code Block |
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language | bash |
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title | Create a New Env from Existing Env |
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conda create --name=<new_env_name> |
Search Packages in All Default Channels
Code Block |
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conda search openblas |
Search Packages in a Specific Channel
Code Block |
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conda search openblas -c conda-forge |
Note: If you want to use your own conda env in hal-ondemand, you need to install conda install ipykernel
.
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 .