how do I run this wizard? is this wizard train's or aws's?

I mean I don't get how all the pieces add up

but the task pending says its in the queue

I was refering to what is the returned object of Task.artifacts['...'] - when I call .get I understand what I get, I'm asking because I want to see how the object I'm calling .get on behaves

one sec

What about permissions to the machines that are being spun up? For exampel if I want the instances to have specific permissions to read/write to S3 for example, how do I mange those?

CostlyOstrich36

it's double weird, because also a task that the pipeline says is "in progress" is actually completed

First of all I wasn't aware that was an option - but I think it's preferable to be able to do it through the command line. Because I'm developing the pipeline to be executed remotely, but for debugging I run it locally.

Using what you showed I can obviously write it, and delete it once it is ready, and rewrite it when I'm debugging or adding features - but I think DX-wise it would be nicer to be able to trigger this functionality through the command line

thx! i was looking in the docs and was looking for something like URL/URI now i know why i didnt find it 😅

AgitatedDove14 UnevenDolphin73

I don't know, I'm the one asking the question 😄

the link to manual model registry doesn't work

💪

see gif:

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:

happens on my phone as well :man-facepalming:

awesome 💪

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?

same result

Happens on my Firefox aswell

SuccessfulKoala55 ⬆ sorry for the delay, was at a meeting

I had to restart the agent and now everything is fine

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