Indeed, sleep() did the trick but it's going into the Debug Samples tab and not the Plots, any reason why? Earlier (with Task.init() followed by Task.get_task() ) the same plt plots got reported to 'Plots'.

0.16.1-320

you mean 0.16?

Ah my bad, I picked up the version from docker-compose file :D

AgitatedDove14 , here's the code snippet you requested

Great! Thanks for the clarification AgitatedDove14 🙂

Right, parsing the TB is too much work, I'll look into the material you sent. Thanks!

I tried it about 2-3 months ago with trains-init (same use-case as this one) and it failed that time too.

Could it be the credentials are actually incorrect?

Highly unlikely, like I said, I generated a new set of credentials from the Web-UI and it worked perfectly fine for an Azure VM (not under the VPN).

Ran it, but it gave no output (but it does say ran successfully)

2021-02-08 18:49:25,036 - clearml - WARNING - InsecureRequestWarning: Certificate verification is disabled! Adding certificate verification is strongly advised. See: Retrying (Retry(total=239, connect=240, read=239, redirect=240, status=240)) after connection broken by 'ReadTimeoutError("HTTPSConnectionPool(host='X.Y.Z.W', port=8015): Read timed out. (read timeout=3.0)",)': /auth.loginGot this, times out after 5 tries

Oh! With the sleep() function? Let me try it again

No, the sample code I sent above works as intended, uploads to 'Plots'. But the main code that I've written, which is almost exactly similar to the sample code behaves differently.

Thanks 🙂

I tried it, and it is uploading it to Debug Samples ( Task.get_task() ) with task.get_logger().report_matplotlib_figure() , but with a Task.init() , it's uploading it to Plots.

Checking with the RC package now

This is odd could it be it automatically forwards to https

I have to check with my IT Team if there's any forwarding

What if I just copy a clearml.conf file and edit out the tokens? Could that work?

It is http btw, i don't know why it logged https://

` * Trying X.Y.Z.W:8080...

• TCP_NODELAY set
• Connected to X.Y.Z.W (X.Y.Z.W) port 8008 (#0)

GET /debug.ping HTTP/1.1
Host: X.Y.Z.W:8080
User-Agent: curl/7.68.0
Accept: /

• Mark bundle as not supporting multiuse
  < HTTP/1.1 302 Found
  < Location:
  < Connection: close
  < X-Frame-Options: SAMEORIGIN
  < X-XSS-Protection: 1; mode=block
  < X-Content-Type-Options: nosniff
  < Content-Security-Policy: frame-ancestors
  <
• Closing connection 0 `

No, those env variables aren't set.

Thanks AgitatedDove14 , I'll go through these and get back to you

I see this AgitatedDove14

It's going to Debug Samples with the RC too

It says container name is optional in azure.storage , if I don't provide the container name, and remove it from the end of default_uri , would that work?

AgitatedDove14 Yes

Verifying credentials ... Error: could not verify credentials: key=xxxxxx secret=xxxxx Enter user access key:

Yeah I noticed that too! Ports are configured properly in the conf file though

AgitatedDove14 , thanks a lot! I'll get back with a script in a day or two.

trains 0.16.3
trains-server 3.6

Hey SuccessfulKoala55 , I'm new to Trains and want to setup an Azure Storage Container to store my model artifacts. I see that we can do this by providing an output_uri in Task.init() but is there another way to send all the artifacts to Azure instead of using the Task.init()? Like setting a variable somewhere, so that whenever I run my tasks I know the artifacts will get stored in Azure even if i dont provide an output_uri

Yes, copied and pasted the configuration file correctly, points to the right server (running on Azure). I created a clearml.conf file on another Azure VM (not under the VPN) and there it worked fine. The 'on-premise' server fails to connect to the ClearML server because of the VPN I think

Basically, set my Host storage as Azure

Yep it does, thanks AgitatedDove14 :)

AgitatedDove14 , is there a way to set the default output URI flag so that if and when a new user creates a clearml.conf the URI is already in it? I was hoping that there's a universal flag somewhere. Asking this because I want all the Models and Artifacts to be stored in one place and the users shouldn't have to edit their configuration files.