Yes, I have a metric I want to monitor so I will be able to sort my experiments by it. It is logged in this manner
logger.report_scalar(title='Mean Top 4 Accuracy', series=ARGS.model, iteration=0, value=results['top_4_acc'].mean())
When looking at my dashboard this is how it looks
my current version of the images used:
By the examples I figured out this ould appear as a scatter plot with X and Y axis and one point only.. Does it avoid that?
I guess what I want is a way to define environment variables in agents
I suspect that it has something to do with remote execution / local execution of pipelines, because we play with this , so sometimes the pipeline task itself executes on the client, and sometimes on the host (where the agent is also)
I believe that is why MetaFlow chose conda as their package manager, because it can take care of these kind of dependencies (even though I hate conda 😄 )
doesn't contain the number 4
Hi guys, just updated the issue - seems like the new release did fix the color scale, but I notice some data points are missing (the plot is missing data!)
see my comment on the issue
https://github.com/allegroai/clearml/issues/373#issuecomment-894756446
TimelyPenguin76 , this can safely be set to s3:// right?
I dont think that has to do anything with the value zero, the lines that should come out of 'mean' and 'median' have the value of None under quantile, but have a dre_0.5 assoxiated with them. those lines appear in the notebook and not in the ui
` alabaster==0.7.12
appdirs==1.4.4
apturl==0.5.2
attrs==21.2.0
Babel==2.9.1
bcrypt==3.1.7
blinker==1.4
Brlapi==0.7.0
cachetools==4.0.0
certifi==2019.11.28
chardet==3.0.4
chrome-gnome-shell==0.0.0
clearml==1.0.5
click==8.0.1
cloud-sptheme==1.10.1.post20200504175005
cloudpickle==1.6.0
colorama==0.4.3
command-not-found==0.3
cryptography==2.8
cupshelpers==1.0
cycler==0.10.0
Cython==0.29.24
dbus-python==1.2.16
decorator==4.4.2
defer==1.0.6
distlib==0.3.1
distro==1.4.0
distro-info===0.23ubuntu1
doc...
Actually I removed the key pair, as you said it wasn't a must in the newer versions
but using that code - how would I edit fileds?
Okay Jake, so that basically means I don't have to touch any server configuration regarding the file-server on the trains server. It will simply get ignored and all I/O initiated by clients with the right configuration will cover for that?
Let's take a step back. Let's remove the clearml-services from the docker compose for a second, and run it manually (then you can control everything). Once you have it running manually, let's try to replicate the setup back to the docker compose, make sense ?
I'd prefer not to docker-compose down as researchers are actively working on it, what do you say that I will manually kill the services agent and launch one myself?
whatttt? I looked at config_obj didn't find any set method
I re-executed the experiemnt, nothing changes
