4.11.5 Upload the Conda environments to an Object Storage bucket associated with the Autonomous AI Database

There is one Object Storage bucket for each data center region. The Conda environment is saved to a folder in Object Storage corresponding to the tenancy and database. The folder is managed by Autonomous AI Database and is only available to users through Oracle Machine Learning Notebooks. There is an 8G maximum size for a single Conda environment, and no size limit on Object Storage.

This topic shows how to upload a Conda environment to the Object Storage bucket associated with the Autonomous AI Database instance using the upload command. You will provide environment descriptions and tags, one for the user name and one for the application name. You will also overwrite any environment with the same name if it exists. The application tag is required for use with embedded execution. For example, OML4Py embedded Python execution works with Conda environments containing the OML4PY tag.
To upload a Conda environment to the Object Storage bucket:
  1. In a Conda paragraph in your notebook, run the following command to upload the mypyenv to the Object Storage bucket associated with the Autonomous AI Database.
    upload mypyenv --overwrite --description 'Install Python seaborn and tensorflow packages' -t user 'OMLUSER' -t application OML4PY
    In this command, you use the upload command and provide the following:
    • --description: a description of your task.
    • -t: A tag for the user OMLUSER and for the application OML4PY.

    Figure 4-48 Command to load the Conda environment for Py


    Command to load the Conda environment for Py

  2. Now, run the following command to view the list of saved environments in mypyenv:
    list-saved-envs -e mypyenv
    The command returns the following:

    Figure 4-49 View saved environment mypyenv


    View saved environment mypyenv

  3. Now upload the myrenv to the object storage by running the following command in a Conda paragraph:
    %conda

upload myrenv --overwrite --description 'Install R forecast and ggplot2 packages' -t user 'OMLUSER' -t application 'OML4R
    The command returns the following:

    Figure 4-50 Command to upload Conda environment for R


    Command to upload Conda environment for R to Object Storage

  4. Again, run the following command to view the list of saved environments in myrenv:
    %conda

list-saved-envs -e myrenv
    The command returns the following:

    Figure 4-51 View saved environment myrenv


    View saved environment myrenv

This completes the task of uploading the Python and R environments mypyenv and myrenv to the Object Storage associated with the Autonomous AI Database. The environments are now available for you to download and use. The environments will remain in the Object Storage until it is deleted.

Parent topic: Use the Conda Interpreter in a Notebook Paragraph