` * 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 `

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

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

I see this AgitatedDove14

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.

` 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...

Okay! Thanks 😄

Basically, set my Host storage as Azure

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://

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.

Okay, my bad, the code snippet I sent is correctly uploading it to 'Plots' but in the actual script I use this:
` def plot_graphs(input_df,output_df,task):

# Plotting all the graphs
for metric in df_cols:


    # Assigning X and Y axes data
    in_x = input_df["frameNum"]
    in_y = input_df[metric]
    out_x = output_df["frameNum"]
    out_y = output_df[metric]

    # Creating a new figure
    plt.figure()

    plt.xlabel('Frame Number')
    ...

AgitatedDove14 Yes

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

Great! Thanks for the clarification AgitatedDove14 🙂

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

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

No, those env variables aren't set.

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

It's going to Debug Samples with the RC too

Thanks 🙂

Oh it worked! I did the pip install multiple times earlier, but to no avail. I think it's because of the env variables? Let me try to unset those and provide it within the trains.conf

Should we also provide credentials for the Storage Account on the Web UI under 'Profile' section?

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...

` 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/VirtualEnvs/test/lib/python3.8/site-...

I did that, and it works flawlessly. I swear I installed the Azure blob storage package multiple times, anyway thanks a lot again for the detailed debugging O:)

Thanks a lot SuccessfulKoala55 🙂

This is what I get with the ' https:// ' , this is atleast getting a response from Azure
` 2020-12-03 13:48:49,667 - trains.Task - INFO - No repository found, storing script code instead
TRAINS results page: http://<IP>:8080/projects/<hash>/output/log
2020-12-03 13:48:51,505 - trains.Task - INFO - Waiting for repository detection and full package requirement analysis
2020-12-03 13:48:53,315 - trains.Task - INFO - Finished repository detection and package analysis
2020-12-03 13:48:53,315 -...

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