https://github.com/allegroai/clearml/commit/164fa357ed01704b11db67b8a7ac19791fbc49d1

This works. So it is still in master and should be included in 1.0.5?

I think it's related to the fix that use "incremental: true", this seems to fix 1 problem, but at the same time it will ignore all other handlers.

Hi, just to be clear, self hosted option is still available right? I need to know this as we have spent some effort on integrating Trains internally and expect to continue the development for a while.

ok, it makes sense. Is there a way to let trains save it without blocking the program ?

I want the support for click as well, or is there any adhoc solution?

Hi, just wanted to check in

thus seeing that user:local-xxxxx

No, I mean it capture the plot somehow, as you can see the left side there are a list of plot, but it does not show up.

I don't want user making heavy requests

for workaround, I write a function to recursive cast my config dictionary into string if needed.

SuccessfulKoala55 task.connect()

I see, I will look into the documentation of it, thanks Jake.

thanks!

potentially both, but let just say structure data first, like CSV, pickle (may not be a table, could be any python object), feather, parquet, some common data format

using configuration directly it actually worse than using a dictionary for hyperparmaeters. It would do the diff line by line (notice the right experiment)

Hi, I think I can confirm this is a bug of Trains. Is that ok if I submit a PR to fix this?

I tried pass the dictionary but the output is not ideal. I would want to have some nested dict like the "execution" > "Source" layout.

As number of parameters can be large, having some hierarchy in the UI will be much easier for comparison

I am not sure what's the difference of logging with "configuration" and "hyperparameters", for now , I am only using it as logging, I guess hyperparmeters has special meaning if I want to use "trains" for some other features.

I use Yaml config for data and model. each of them would be a nested yaml (could be more than 2 layers), so it won't be a flexible solution and I need to manually flatten the dictionary

In this case, I would rather use task.connect(), diff line by line is probably not useful for my data config. As shown in the example, shifting 1 line would result all remaining line different.

But this also mean I have to first load all the configuration to a dictionary first.

Thanks for your help. I will stick with task.connect() first. I have submit a Github Issue, thanks again AgitatedDove14

AgitatedDove14
I get this log but there is nothing show up in the UI.

2020-09-10 09:15:06,914 - trains.Task - INFO - Waiting for repository detection and full package requirement analysis ======> WARNING! UNCOMMITTED CHANGES IN REPOSITORY origin <====== 2020-09-10 09:15:10,378 - trains.Task - INFO - Finished repository detection and package analysis

TimelyPenguin76 No, I didn't see it.

repository detection is fine

let me know how can I provide better debug message

This log does not always show up, even tho it is logged when I run it on Machine B. In contrast, I run it on Machine A, this message did show up, but nothing is logged.

` 2020-09-10 09:15:06,914 - trains.Task - INFO - Waiting for repository detection and full package requirement analysis
======> WARNING! UNCOMMITTED CHANGES IN REPOSITORY origin <======
2020-09-10 09:15:10,378 - trains.Task - INFO - Finished repository detection and package ...

I create a fresh conda env and install python for both machine

one does record the package, the other does not

conda create -n trains python==3.7.5
pip install trains==0.16.2.rc0

yes

CumbersomeCormorant74 Thanks for the reply. Let me clarify, I mean reordering the columns (dragging the column).
If the drag defaults columns, and hit F5, the order is preserved. However, if you try adding a metric column to be the first column and hit F5, it will not be preserved.