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Conda Installation

CUDA 12.1 Bug

Due to a known bug with CUDA versions greater than 12.1, executing compiled models on Orin Jetpack 5.X may fail.

Cross Compilation Support

Cross compilation allows users to compile for a aarch64 device (say Jetson or Raspberry Pi) on an x86_64 host device (say Intel or AMD CPU). If you wish to compile for aarch64 you will need to install g++-aarch64-linux-gnu. You can use APT to install this on Ubuntu systems:

sudo apt-get install -y g++-aarch64-linux-gnu

1. Access Latent AI's Container Repository

In order to pull containers or install packages from Latent AI, you'll need to create a personal access token. To do so, follow these steps:

i. Login to the Latent AI Repository

  • Click the Sign in link in the upper right.
  • Select Sign In with SSO.
  • Enter your access credentials.

ii. Create your Personal Access Token

  • Click on your profile in the upper right.
  • Select User Token on the left navigation.
  • Select the Access user token button.
  • View your user token name and user token pass code.

You can export the token name and token pass code as environment variables:

export REPOSITORY_TOKEN_NAME=<user_token_name>
export REPOSITORY_TOKEN_PASSCODE=<user_token_pass_code>

2. Export License Key

You should have received this via email.

Tip

You can persist variables like LICENSE_KEY across bash sessions by placing them in your ~/.bashrc file.

export LICENSE_KEY=key/<license key>

3. Create and Activate conda Environment

Copy or download the following environment.yml:

name: latentai
channels:
  - nvidia/label/cuda-12.1.0
  - conda-forge
  - defaults
dependencies:
  - jupyter
  - libstdcxx-ng
  - nvidia::cuda-tools
  - python=3.10
  - pip
  - pip:
      - --extra-index-url https://${REPOSITORY_TOKEN_NAME}:${REPOSITORY_TOKEN_PASSCODE}@repository.latentai.com/repository/pypi/simple
      - leip-design

Then run the following command to create the conda environment:

conda env create -f environment.yml

A new environment will be created in your conda installation called latentai which you can activate with the following command:

conda activate latentai