hparams: fix the parallel coordinate layout #4988
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Bug
---
Previously, we were setting the width of the container based on count of
all hparams and metrics without considering the visibility. This had
caused the UI to be in very awkward state where each visible hparams and
metrics are spaced a lot even if the selection count is quite low.
Fix
---
We layout the parallel coordinates based on number of visible
{hparam,metric}s. The change is a bit larger because:
- I had to add type information and refactor it a little for
understanding the code.
- Undo the performance optimization where we do not mutate the layout
unless important piece of information in the configuration has
changed. To detect the old confiugration vs. new configuration, we
have to now remember an additional state in the component.
Fixes tensorflow#3414.
psybuzz
approved these changes
May 19, 2021
|
@stephanwlee @psybuzz is this released yet im having these issues with 2.5.0. Thanks! |
|
Thanks for the ping. The fix will be part of the upcoming TensorBoard 2.6.0 (and TensorFlow 2.6.0) release, so please stay tuned. The TB cadence has roughly matched the TensorFlow release cadence, so the ETA is soon (on the order of days/weeks from now, not months). If you're in need of this fix immediately, it should be available in https://pypi.org/project/tb-nightly/ right now. |
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Bug
Previously, we were setting the width of the container based on count of
all hparams and metrics without considering the visibility. This had
caused the UI to be in very awkward state where each visible hparams and
metrics are spaced a lot even if the selection count is quite low.
Fix
We layout the parallel coordinates based on number of visible
{hparam,metric}s. The change is a bit larger because:
understanding the code (minimally added the types).
unless important piece of information in the configuration has
changed. To detect the old configuration vs. new configuration, we
have to now remember an additional state in the component.
Fixes #3414.
Previous:
New:
