Base Image

nvcr.io/nvidia/pytorch

The base image used in this Dockerfile is defined by the following ARG and FROM instructions:

ARG BASE_IMAGE=nvcr.io/nvidia/pytorch
ARG BASE_TAG=24.02-py3

FROM ${BASE_IMAGE}:${BASE_TAG} as base

The base image is an NVIDIA PyTorch image, specifically nvcr.io/nvidia/pytorch with the tag 24.02-py3.

This image is pulled from the NVIDIA Container Registry (nvcr.io).

NVIDIA PyTorch Image

• The NVIDIA PyTorch image is a pre-built Docker image provided by NVIDIA.

• It comes with PyTorch and its dependencies pre-installed, optimized for NVIDIA GPUs.

• The image is based on Ubuntu and includes CUDA, cuDNN, and other NVIDIA libraries necessary for GPU acceleration.

Tag 24.02-py3

• The tag 24.02-py3 specifies the version of the NVIDIA PyTorch image.

• The 24.02 part indicates the release version of the image, which corresponds to the year and month of the release (February 2024 in this case).

• The py3 suffix indicates that the image uses Python 3.

NVIDIA Container Registry (nvcr.io)

• NVIDIA maintains its own container registry called NVIDIA Container Registry (nvcr.io).

• The registry hosts various GPU-optimised Docker images, including the PyTorch image used in this Dockerfile.

• Using an image from nvcr.io ensures that the image is compatible with NVIDIA GPUs and includes the necessary NVIDIA software components.

Benefits of using the NVIDIA PyTorch base image

• Pre-installed PyTorch: The image comes with PyTorch pre-installed, saving the effort of installing it manually.

• GPU Optimisation: The PyTorch installation in the image is optimised for NVIDIA GPUs, providing better performance out of the box.

• NVIDIA Libraries: The image includes NVIDIA libraries such as CUDA and cuDNN, which are required for GPU acceleration.

• Reproducibility: Using a pre-built image ensures a consistent environment across different machines and deployments.

By using the NVIDIA PyTorch image as the base, the Dockerfile leverages the pre-configured environment and optimisations provided by NVIDIA.

This saves time and effort in setting up the necessary dependencies and ensures compatibility with NVIDIA GPUs.

The as base part of the FROM instruction creates a named build stage called base.

This allows subsequent stages in the Dockerfile to refer to this stage and use it as a starting point for further customisation.