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November 1, 2019 at 6:20am
For me too. I cannot start new experiment, it seems the client authorization is broken.
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hi - our team is currently investigating those issues. I will let you know as soon as I have an answer to what has happened.
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Hi , , ! Sorry everyone for the issues you experienced. We had a configuration error that we introduced a few days ago and it took some time to blow up (also, in a fashion that was not obvious to notice and track down). This has been fixed today. Hopefully, everything is back to normal. Please let me know if you experience those symptoms again!
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Thank you! Confirming I'm able to successfully hit the API.
Edited
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November 2, 2019 at 11:52am
Thx for fixing that. Actually, I was surprised to find out that the experiments that were running recovered after such a long gap and eventually and the data are again sent to the server. This is very nice although: 1) There is still a gap in the data (I could imagine that you could make a long buffering so there is no gap) 2) The status of the runs is "failed". Well, they are not failed anymore, now in a kind of "recovered" state but rather "running" than "failed".
Btw. I love that I can abort a run from GUI! There is only a small problem - AFAIR if I move some runs to trash then they are automatically aborted, aren't they? Aborting runs requires confirmation which is good but moving them to trash doesn't require any confirmation. I think that in case of moving running jobs to trash I should be asked for a confirmation.
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November 9, 2019 at 9:53pm
Any one experiencing issues while creating experiment that upload source files? They are stuck for me (likely connection issues)
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creating one without uploading source works fine
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Hi I do not encounter such problems. Does the problem still occur? There could be some temporary connection issues but it does not look like the case in the moment. How exactly your method call looks like?
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December 13, 2019 at 5:18pm
Hi. Is it possible to log multi-series data and see it in one chart? for example average precision per label.
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December 14, 2019 at 3:19pm
You can log metrics for precison_class1, precision_class2 ... to separate channels and later combine them into one channel via chart sets. I've done something like that in chart set auc with channels train_iter_auc valid_iter_auc. https://ui.neptune.ml/neptune-ml/credit-default-prediction/e/CRED-80/charts Does that help?
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Thanks . That can work but it's very tedious as I have 35 classes. Would make more sense to add a "series" param to log_metric e.g. neptune.log_metirc(metric='AP', series='cat', value=0.8)
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It is a good proposal. As a matter of fact we are actually working on chart sets right now. I think may talk to about that soon.
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There is an alternative option.
You can fetch your experiment via query api. Create charts and log it. Something like:
from neptune.sessions import Session
project = Session().get_project('neptune-ml/credit-default-prediction')
exp = project.get_experiments(id=['CRED-55'])[0]
fig, ax = plt.subplots()
for name in class_names:
df = exp.get_numeric_channels_values('precision_{}'.format(name))
ax.plot(df.x, df['precision_{}'.format(name)], label=name)
plt.legend()
fig.savefig('precision_per_class.png')
exp.log_image('precision_per_class', `precision_per_class.png')
There is also send_figure helper method in neptune-contrib to make it a bit simpler.
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I hope this helps
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January 14, 2020 at 3:50pm
Hi I am new in neptune. Now I wonder can we create 3d plots in neptune? for example, I have a 2D position (x, y) and 'z' which is the result of my network.
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January 15, 2020 at 7:32pm
Hi, I have a quick question about running xgboost models in neptune using R. For params, can I say model = "xgbTree" and metric = 'tweedie-nloglik@1.2'? The experiment always failed. Any examples of this kind of algorithm that I can take a look? Thanks!
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Hi, I have a quick question about running xgboost models in neptune using R. For params, can I say model = "xgbTree" and metric = 'tweedie-nloglik@1.2'? The experiment always failed. Any examples of this kind of algorithm that I can take a look? Thanks!
Could you please paste the code that produces errors? Or the error message itself?
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I just noticed there is a typo in R-support docs:
params = list(metric="Accuracy",
tuneLength=100,
model="rf",
searchMethod="random",
cvMethod="repeatedcv",
cvFolds=2,
cvRepeats=1)
# Create experiment
neptune$create_experiment(params=paramsd)
it should be
neptune$create_experiment(params=params)
Is that it by any chance?
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January 16, 2020 at 5:00pm
Could you please paste the code that produces errors? Or the error message itself?
Hi Probably not because of the typo. I used neptune$create_experiment(name='training on mtcars', params=params, properties=list( data_version=digest(dataset)), tags=c('mtcars', 'xgboost'), upload_source_files=list('train_random_forest.R') instead of neptune$create_experiment(params=params)
The code doesn't produce any error in R, but the experiment failed on neptune, where can I find the error details on neptune?
Edited
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January 17, 2020 at 1:18pm
hey thanks for reaching out
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You can look for an error message in the stdout and stderr in the monitoring tab in the experiment. Take a look at the screen below
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Hi Here is the screenshot in my monitoring tab. What does this error means?
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Hey -> on the screen you posted, there is (unfortunately) no signs of errors. Let's move further discussion to the direct conversation.
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