The image has been added to the images in Sagemaker and I am able to use it in Sagemaker notebooks. However, when launching a notebook job, I get Exception during processing notebook: No such kernel named conda-env-customenv-py.
SageMaker will inject the directory where your model files and sub-directories, saved by save, have been mounted. Your model function should return a model object that can be used for model serving.
SageMaker Studio is, in essence, just a theme for Jupyter with a few added features. In the below diagram, you can see that your Studio interface and files are hosted by the " JupyterServer App ", while the instances that execute your code are separate machines running containers.
I'm using Sagemaker in AWS Sagemaker Studio to try to run training jobs in script mode. Below is an example code snippet I'm trying to run: from sagemaker.xgboost.estimator import XGBoost est = XGB...
I have installed miniconda on my AWS SageMaker persistent EBS instance. Here is my starting script: #!/bin/bash set -e # OVERVIEW # This script installs a custom, persistent installation of conda...
Workaround: Instead of mounting your old EFS, you can mount the SageMaker studio EFS onto an EC2 instance, and copy over the data manually. You would need the correct EFS storage volume id, and you'll find your newly copied data available in Sagemaker Studio. I have not actually done this though. To find the EFS id, look at the section "Manage your storage volume" here.
the new sagemaker UI doesn't seem to list the GPU images I don't think this is a SageMaker Studio Notebook its a Sagemaker Notebook Instance which is the oringal sagemaker notebook environment (where both the notebook and kernel run on the same "machine".
It is not possible to install docker in the SageMaker Studio. Is there a way to install and use it? $ sudo yum install docker Loaded plugins: ovl, priorities No package docker available.
I have a Sagemaker Jupyter notebook instance that I keep leaving online overnight by mistake, unnecessarily costing money... Is there any way to automatically stop the Sagemaker notebook instance...
SAGEMAKER_PROGRAM should be set to the name of the serving script, e.g. 'sagemaker_serve.py' These are specified under the 'Environment' section part of each entry in the 'Containers' section.
