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.

AgitatedDove14 Thanks! This seems to be a more elegant solution

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

I want a reliable way, so I don't want to hardcode to check if trains.conf exist in a certain path

.netrc <- seems wandb use this

I don't want to mess with the standard setup.

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

This will cause a redundant Trains session, I guess.

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.

AgitatedDove14 Let me share the exact code and commit and entry point to you later. Thanks!

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

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.

I am interested in machine learning experiment mangament tools.

I understand Trains already handle a lot of things on the model side, i.e. hyperparameters, logging, metrics, compare two experiments.

I also want it to help reproducible. To achieve that, I need code/data/configuration all tracked.

For code and configuration I am happy with current Trains solution, but I am not sure about the data versioning.

So if you have more details about the dataset versioning with the enterprise offer...

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

GrumpyPenguin23 yes, those features seems to related to other infrastructure, not Trains (ML experiment management)

I wonder what's the extra features is offered in the enterprise solution tho

but somewhere along the way, the request actually remove the header

I am trying to debug locally

I just remove it and it works now.. LOL

🙂 Nice debugging experience

so... the VM IP is there

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...

I mean, once I add environment variable, can trains.conf overwrite it? I am guessing environment variable will have a higher hierarchy.

The things that I want to achieve is:
Block user to access to public server If they configure trains.conf, then it's fine

import os os.environ["TRAINS_API_HOST"] = "YOUR API HOST " os.environ["TRAINS_WEB_HOST"] = "YOUR WEB HOST " os.environ["TRAINS_FILES_HOST"] = "YOUR FILES HOST "

is that possible?

It seems that I do receive the bearer token

I can confirm this seems to fix this issue, and I have reported this issue to kedro team see what's their view on this. So it seems like it did remove the TaskHandler from the _handler_lists

really appreciate the help along the way... I have taken way too many of your time

not today tho, I am too tired already