I am working in AWS Sagemaker Jupyter notebook. I have installed clearml package in AWS Sagemaker in Jupyter. ClearML server was installed on AWS EC2. I need to store artifacts and models in AWS S3 bucket, so I want to specify credentials to S3 in clearml.conf file. How can I change clearml.conf file in AWS Sagemaker instance? looks like permission denied to all folders on it. Or maybe somebody can suggest a better approach.
ClearML how to change clearml.conf file in AWS Sagemaker
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Disclaimer I'm part of the ClearML (formerly Trains) team.
To set credentials (and
clearml-server
hosts) you can useTask.set_credentials
. To specify the S3 bucket as output for all artifacts (and debug images for that matter) you can just set it as thefiles_server
.For example:
To pass your S3 credentials, just add a cell at the top of your jupyter notebook, and set the standard AWS S3 environment variables: