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  1. Red Hat OpenShift Data Science
  2. RHODS-845

[SPIKE] gather information on package versions for the notebook image with details

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    • v1.0.13
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      We need to have a clear view on supported packages across images that we can communicate to customers. If certain images need to have different versions of packages, we need to be able to explain why to customers. We should start with the goal of consistency across images and only move away from that if there is some technical barrier related to compatibility.
       
       For example currently:
       
      For example:

      • in Std. DS, we have Matplotlib 3.1.3, Numpy 1.20.2, Pandas 1.2.3
      • in PyTorch, we have Matplotlib 3.4.1, Numpy 1.20.2, Pandas 1.2.3
      • in TensorFlow, we have Matplotlib 3.1.3, Numpy 1.19.5, Pandas 0.25.3
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      We need to have a clear view on supported packages across images that we can communicate to customers. If certain images need to have different versions of packages, we need to be able to explain why to customers. We should start with the goal of consistency across images and only move away from that if there is some technical barrier related to compatibility.    For example currently:   For example: in Std. DS, we have Matplotlib 3.1.3, Numpy 1.20.2, Pandas 1.2.3 in PyTorch, we have Matplotlib 3.4.1, Numpy 1.20.2, Pandas 1.2.3 in TensorFlow, we have Matplotlib 3.1.3, Numpy 1.19.5, Pandas 0.25.3
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    • MODH Sprint 23

      We need to have consistency across notebook package versions as described in the acceptance criteria. However, the first step is to simply gather information about the common packages across the various notebooks so that we can decide which packages to track.

      This is being done here https://docs.google.com/spreadsheets/d/1uNKUqnAo1FUuIZFj5ugQJEhk9DREk1tEKfc8jy10UfY/edit#gid=0

      (this was originally a bug, changed it to a "spike" story).

              tmckay@redhat.com Trevor Mckay (Inactive)
              hnalla Harshad Reddy Nalla
              Pablo Felix Pablo Felix (Inactive)
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