if you go here https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_aws_ec2_ami you can see you can launch a community ami and if you go here https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_aws_ec2_ami/#clearml-server-aws-community-amis you will see the list of community AMI’s you can launch

i think the call is wrong

yeah

you can use Task.update_output_model() to update the name of the output moel

https://clear.ml/docs/latest/docs/references/sdk/task#update_output_model

not sure if it will work but its worth a try

alternatively you could create a new OutputModel like here: https://github.com/allegroai/clearml/blob/master/examples/reporting/model_reporting.py , not sure if there is a way to stop the automatic uploading

ahh i see so one Task has multiple models that are trained

i.e.
Task.update_output_model(name="custom_model")

it requires you set the weights and the framework name

@<1523701827080556544:profile|JuicyFox94> thanks for the reply, I’ll create a github issue 🙂 !

None

model*

sure where do i patch it?

Failed processing request http://localhost:8008/auth.login : 'Logger' object is not callable

SuccessfulKoala55 do you mean request_handlers.py

should it be http://log.info (...)

` [2022-08-18 20:58:49,892] [9] [INFO] [clearml.request_handlers] GET
[2022-08-18 20:58:49,895] [9] [INFO] [clearml.request_handlers] Basic NUtORklQWUIzM0tIVUFRNUI4SkM6eU4yUXE4RTNvWDlpYlBRVmF1NEpiQXZQMHlUdHozNUluZVY4ZkpuZXNTRnRYbmRlR3I=
[2022-08-18 20:58:49,904] [9] [INFO] [clearml.service_repo] Returned 200 for auth.login in 6ms
[2022-08-18 20:58:50,059] [9] [INFO] [clearml.request_handlers] GET
[2022-08-18 20:58:50,060] [9] [INFO] [clearml.request_handlers] Basic NUtORklQWUIzM0tIVUFRNUI4SkM...

i'm looking at the server.py file and it doesn't have call = self. create_api_call(request)

i got these extra logs

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

^ self hosted @<1523701070390366208:profile|CostlyOstrich36>

Name: clearml
Version: 1.9.1

going to double check that rn

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

still*

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 ...