Pull Prebuilt Containers
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Pull Prebuilt Containers¶
Prebuilt containers are provided in:
Intel Gaudi vault
Amazon ECR Public Library
AWS Deep Learning Containers (DLC)
Pull and Launch Docker Image - Intel Gaudi Vault¶
Note
Before running Docker, make sure to map the dataset as detailed in Map Dataset to Docker.
Use the below commands to pull and run Dockers. Make sure to update the below command with the required operating system. See the Support Matrix for a list of supported operating systems:
docker pull vault.habana.ai/gaudi-docker/1.18.0/{$OS}/habanalabs/pytorch-installer-2.4.0:latest
docker run -it --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --net=host --ipc=host vault.habana.ai/gaudi-docker/1.18.0/{$OS}/habanalabs/pytorch-installer-2.4.0:latest
Note
Include –ipc=host in the Docker run command for the Docker images. This is required for distributed training using the Habana Collective Communication Library (HCCL); allowing re-use of host shared memory for best performance.
To run the Docker image with a partial number of the supplied Gaudi devices, make sure to set the Device to module mapping correctly. See Multiple Dockers Each with a Single Workload for further details.
Amazon ECR Public Gallery¶
To pull and run Docker images from Amazon ECR Public Library, make sure to follow the steps detailed in Pulling a public image.
AWS Deep Learning Containers¶
To set up and use AWS Deep Learning containers, follow the instructions detailed in AWS Available Deep Learning Containers Images.