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We Have A Use Case Where An Experiment Consists Of Multiple Docker Containers. For Example, One Container Works On Cpu Machine, Preprocesses Images And Puts Them Into Queue. The Second One (Main One) Resides On Gpu Machine, Reads Tensors And Targets From
Pipelines! 😄
ClearML allows you to create pipelines, with each step either being created from code or from pre-existing tasks. Each task btw. can have a custom docker container assigned that it should be run inside of, so it should fit nicely with your workflow!
Youtube videos:
https://www.youtube.com/watch?v=prZ_eiv_y3c
https://www.youtube.com/watch?v=UVBk337xzZo
Relevant Documentation:
https://clear.ml/docs/latest/docs/pipelines/
Custom docker container per task:
https://clear.ml/docs/latest/docs/references/sdk/task#set_base_docker
You can also override the docker container it should use by using an override in the pipeline controller
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2 years ago
one year ago