I have to admit, I haven't had the time 😞
Trying to get pip to be twice as fast 🤞
https://github.com/pypa/pip/pull/8215
Please keep pinging me, I would really like to follow on it.
This should have worked with the latest clearml RC.
And you verified it is not working?
MagnificentSeaurchin79 no need for the detection api (yes definitely a mess to setup), it will be more helpful to get a toy example.
I don't think so..I had a problem before 0.17.5
@ https://app.slack.com/team/U01J3C692M8 where you able to come up with a solution?
This looks strange that only a single scalar is reported.
Thanks MagnificentSeaurchin79 !
Let me check what's the status with this one, could it be the same as this one?
https://github.com/allegroai/clearml/issues/322
BTW MagnificentSeaurchin79 just making sure here:
but I don't see the loss plot in scalars
This is only with Detect API ?
let me know if you need any help/ have issues trying to reproduce...thanks!
Hi AgitatedDove14 ! Were you able to reproduce this?
whereas this is what is being logged in your toy example: tf.Tensor(1742.0144, shape=(), dtype=float32)
Hi MagnificentSeaurchin79
This sounds like a deeper bug (of a sort), I think the best approach is to open a GitHub issue with some code that can reproduce this behavior, or at least enough information so that we could try to catch the bug.
This way we will make sure it is not forgotten.
Sounds good ?
This is only with Detect API ?
I only tested it with the Detect API
Hi MagnificentSeaurchin79
Could you test with the tesnorflow toy example?
https://github.com/allegroai/clearml/blob/master/examples/frameworks/tensorflow/tensorboard_toy.py
I'll need to see how to extract only the part that we care about
It's kind of a pain to setup Tensorflow Object Detection API
<tf.Tensor 'Loss/RPNLoss/localization_loss:0' shape=() dtype=float32
This is what is being logged as scalar in the OD API
MagnificentSeaurchin79 making sure the basics work.
Can you see the 3D plots under the Plot section ?
Regrading the Tensors, could you provide a toy example for us to test ?
yes, that works..but wasn't the issue with logging tensors?