So clearml-init can be skipped, and I provide the users with a template and ask them to append the credentials at the top, is that right? What about the "Credential verification" step in clearml-init command, that won't take place in this pipeline right, will that be a problem?

AgitatedDove14 , I'll have a look at it and let you know. According to you the VPN shouldn't be a problem right?

Thanks 🙂

trains 0.16.3
trains-server 3.6

Yep it does, thanks AgitatedDove14 :)

AgitatedDove14 Yes

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).

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 , 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.

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

This is the whole error dump:
`
2020-12-03 13:31:27,296 - trains.storage - ERROR - Azure blob storage driver not found. Please install driver using "pip install 'azure.storage.blob>=2.0.1'"
Traceback (most recent call last):
File "test.py", line 3, in <module>
task = Task.init(project_name="Test", task_name="debugging")
File "/home/sam/VirtualEnvs/test/lib/python3.8/site-packages/trains/task.py", line 461, in init
task.output_uri = cls.__default_output_uri
File "/home/sam/Virtu...

This is odd could it be it automatically forwards to https

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

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

Basically, set my Host storage as Azure

Okay! Thanks 😄

It's going to Debug Samples with the RC too

Understood, I'll look into it!

My use case is that, let's say I'm training with a file called train.py in which I have Task.init() , now after the training is finished, I generate some more graphs with a file called graphs.py and want to attach/upload to this training task which has finished. That's when I realised Task.get_task() is not working as intended, but it is when I have a Task.init() before it.

AgitatedDove14 , here's the code snippet you requested

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.

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'.

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

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

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

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://

0.16.1-320

you mean 0.16?

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

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

I see this AgitatedDove14

` from trains import Task
import matplotlib.pyplot as plt
import numpy as np
import time

task = Task.get_task(task_id='task_id')

for i in range(0,10):

x_1 = np.random.rand(50)
y_1 = np.random.rand(50)

x_2 = np.random.rand(50)
y_2 = np.random.rand(50)
plt.figure()
plt.scatter(x_1, y_1, alpha=0.5)
plt.scatter(x_2, y_2, alpha=0.5)
# Plot will be reported automatically
# plt.show()
task.get_logger().report_matplotlib_figure(title="My Plot Title", serie...

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