the above represent my case

Here are the logs I got:

well, kind of, I linked the other topic, but it was completely unrelated
this topic is about the issue with reporting a configuration with a string inside a tuple that has backslash

AgitatedDove14 thanks, I actually experimented with similar parallel pool approach but the overhead seem to even out the benefit..
is there something you can think of for the first part though? pulling all the experiments get_top_experiments()

I want a manual way to access a global optimizer from multiple machines, it can be an agent, however the critical part is that machine will be able to pull and report multiple trials without restarting

hi TimelyPenguin76 thanks, for some reason it didn't show up in my search or maybe I missed it..
I was wondering specifically about the following case:
lets say I'm cloning the task you created above, now I am editing some of the hyper parameters in the UI and enqueueing it.
would the config be "automatically" synced? I assume not, if not what would be a recommended way to sync it?
I especially wondered if there is a "smart" sync (with parsing) that can take advantage of the type hinting in...

its only these two files.. nothing else

is there an available reference for how I can use the API calls with the python API? it is not clear to me from what you shared

CostlyOstrich36 , I don't think we are talking about the same things..

AgitatedDove14 , by the way, can you take a look at https://clearml.slack.com/archives/CTK20V944/p1625558368001600
maybe you'll have other ideas? at the moment it seems like a dead end

AgitatedDove14 , TimelyPenguin76 , a small blast from the past
Unfortunately it seems like this is not working for backslash escape character
https://demoapp.demo.clear.ml/projects/7eaa1749475d4ad4bd21a5456fd2e157/experiments/3efe981238e543c8b6ad682dd13c72bc/output/hyper-params/hyper-param/General
https://colab.research.google.com/drive/1w5lQGxsblnLGlhJEDH_b0aIiUvjGeLjy?usp=sharing

Hi AgitatedDove14 , I am using the pre release of hydra together with the latest clearml, and previous clearml server version (I didn't have time yet to update)..
I'm getting similar error to the mentioned in the post:
` 2021-05-06 15:48:07,359 - root - WARNING -
2021-05-06 15:48:07,359 - root - WARNING - File "/home/user/.local/lib/python3.8/site-packages/clearml/backend_api/services/v2_9/tasks.py", line 1067, in description
self.assert_isinstance(value, "description", six.string_typ...

I am actually not sure specifically about \b myself, but even when replacing with . I am getting \. double backslash instead of the single backslash ( for the tuple case ). which in the case of a regexp expression changes the meaning of the expression. the expected behavior would be registering it as single backslash

AgitatedDove14 , in my use case, the strings are regular expressions. If the reported regular expression string changes when reported, it messes up my run.
I can't define the "legal regular expression space", off the top of my head. The expected behavior is reported_string == original_string..

It seems to me that the source of the mismatch is the str(tuple())

CostlyOstrich36 thanks, is there an example for using the post\get in a pythonic way to access the mentioned debug.ping ?

it doesn't even need to be a sub process at this point.. it can be serial execution

AnxiousSeal95 , the roaming people, how can I find them actually?

it is good enough for my current needs, thanks!

TimelyPenguin76 thanks for the answer, so for example (to make sure I understand) with the example you gave above when I'll print the config I'll see the new edited parameters?
What about the second part of the question, would it be parsed according to the type hinting?

the solution you suggested works for the single machine case. The missing part is being able to access and "claim" spawn trials (samples in the HP plane), from multiple machines

The difference is that I want a single persistent machine, with a single persistent python script that can pull execute and report multiple tasks

I get it with the simplest config if I define it as a dataclass, using the example you share as a basis:
config_files/cfg.py
` from hydra.core.config_store import ConfigStore
from dataclasses import dataclass

@dataclass
class MasterConfig:
test: str = 'test'

cs = ConfigStore.instance()
cs.store(name="config", node=MasterConfig) and for the main I had to make some small changes to connect my local server (I'm sharing them just in case): hydra_example.py: # ClearML - Hydra Example

im...

that is the heaviest part for me

and this is how I get the new hyper parameters for the new run

AgitatedDove14
What I'm looking here is some logic that will allow us not to break backwards compatibility on the one hand, but still will allow you to have something like "first\second" entry. WDYT? any ideas? (I really want to make sure we fix it as soon as possible)Do you mean something like the dictionary structure?
I am not sure about a clean elegant solution yet.. but this patch does some of the job:
str('(' + ', '.join([str(elm) for elm in tuple_value])+')')I am actually curio...

the offline error is different

just making sure, the services queue is available from the clearml-server UI

one more question, is there a way to assign a job to a specific worker? or is it only working on queue level

kind of on the same topic, it would be very useful if some kind of verbosity will be enabled.. some kind of progress bar for get_top_experiments()