so... the VM IP is there

not today tho, I am too tired already

It seems that I do receive the bearer token

TimelyPenguin76 No, I didn't see it.

this is a bit weird, I have two Window machine, and both point to the public server.

🙂 Nice debugging experience

wow, new data version feature and session could be useful

AgitatedDove14
The core of Kedro is pipeline (multi-nodes), where you can stitch different pipeline together. For the data part, they use something called DataCatalog, which is a YAML file defined how your file is going to be saved/loaded, and where is the file. Kedro also resolve the DAGs of your pipeline, so you actually don't define what's the order of execution (it's defined by the input/output dependencies). The default is a sequentialRunner, optionally, you can use ParallelRunner where...

AgitatedDove14 Yes, as I found as Kedro's pipeline start running, the log will not be sent to the UI Console anymore. I tried both Task.init before/after the start of kedro pipeline and the result is the same. The log is missing, but the Kedro logger is print to sys.stdout in my local terminal.

Yes, i did use foreground.

I tested in a older "trains" server, it will show up log like this if no job is pick up. While my new "clearml-agent" shows nothing

No tasks in queue bb1bb1673f224fc98bbc8f86779be802
No tasks in Queues, sleeping for 5.0 seconds

Not sure why my elasticsearch & mongodb crashed. I have to remove and recreate all the dockers. Then clearml-agent works fine too

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

may I ask is there a planned release date?

Hi, sorry for really late update.
I finally get some more information about the logging issue. After diving in Kedro source code, I found there was a line that link to the log issue.

logging.config.dictConfig(conf_logging)This line will cause ClearML fail to pick up the log, any idea? AgitatedDove14 SuccessfulKoala55

A snippets to test is available, try commenting the line:6, the log will pop up, when line:6 is enable, event print() is not shown up.

` import logging
from clearml im...

I tried to step in the debugger, I can't quite see the clearml handlers in logging._handlers, the dict is empty, where is the clearml handler stored? AgitatedDove14

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.

I am running on Window 10 Machine, is this not compatible?

it's ok, I don''t think this is very important. thx

Is it possible to set the frequency of sampling?

How often does Trains record the usage? I tried running a dummy programming which sleeps for 20 seconds and I don't see any plot.

Is this configurable?

I also get this from the logging

TRAINS Monitor: GPU monitoring failed getting GPU reading, switching off GPU monitoring

AgitatedDove14 Thanks! This seems to be a more elegant solution

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

is it possible to overwrite if trains.conf did exist

currently I do it in a hacky way. I call trains.backend_api Session, and check if 'demoapp' in web server URL.

Cool! Will have a look at the fix when it is done. Thanks a lot AgitatedDove14

AnxiousSeal95 At first sight, the pipeline logic of ClearML seems binding with ClearML quite a bit. Back then I was considering I need something that can convert to Production pipeline (e.g. Airflow DAGs) easily, as we need pipelines not just for Experiments, Airflow seems to be the default one.

Also, clearml-data was not available when we started the development of internal framework. As for clear-agent, from my previous experience, it seems not working great with Window sometimes, and als...

matplotlib.version
'3.1.3'

The "incremental" config seems does not work well if I add handlers in the config. This snippets will fail with the incremental flag.

` import logging
from clearml import Task

conf_logging = {
"version": 1,
"incremental": True,
"formatters": {
"simple": {"format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s"}
},
"handlers": {
"console": {
"class": "logging.StreamHandler",
"level": "INFO",
"formatter": "s...