^ self hosted @<1523701070390366208:profile|CostlyOstrich36>

Name: clearml
Version: 1.9.1

although i wish it would use the credentials in my clearml.conf file automatically

and when i’m running it in sagemaker

still*

The only difference that i notice is that when i run it locally the task is completed

going to double check that rn

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from clearml import Task

# Connecting ClearML with the current process,
# from here on everything is logged automatically
# Create a new task, disable automatic matplotlib connect
task = Task.init(project_name='Something', task_name='Something')

# Create plot and explicitly report as figure
N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.rand(N)
area = (30 * np.random.rand(N))**2  # 0 to 15 point radii
plt.scatter(x, y, s=area, c=colors, alpha=0.5)
plt.show()

%env CLEARML_WEB_HOST={-----}
%env CLEARML_API_HOST={-----}
%env CLEARML_FILES_HOST=undefined
%env CLEARML_API_ACCESS_KEY={-----}
%env CLEARML_API_SECRET_KEY={-----}

@<1523701070390366208:profile|CostlyOstrich36> yes it indeed shows up when running it locally

Hi @<1523701717097517056:profile|ScantMoth28> , what version of ClearML are you using? Are you using a self hosted server or the community one?

@<1523701070390366208:profile|CostlyOstrich36> maybe cause sagemaker is running in headless mode

^ it works if i do that and use the jupyter credentials from my work space settings.

but none the less I’ll continue with this work around thanks!

And if you run the same code locally everything is reported correctly?

the task is stil running