mxnet

MXNet is a deep learning framework designed for both efficiency and flexibility. It allows to mix the flavors of symbolic programming and imperative programming to maximize efficiency and productivity.

In its core is a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient.

Running mxnet :

Before running the container, use docker pull to ensure an up-to-date image is installed. Once the pull is complete, you can run the container image.

Procedure :

1. In the Tags section, locate the container image release that you want to run.
2. In the Pull column, click the icon to copy the docker pull command.
3. Open a command prompt and paste the pull command. The pulling of the container image begins. Ensure the pull completes successfully before proceeding to the next step.
4. Run the container image. A typical command to launch the container is:

         nvidia-docker run -it --rm -v local_dir:container_dir nvcr.io/nvidia/mxnet:<xx.xx>

Where:

• -it means run in interactive mode
• --rm will delete the container when finished
• -v is the mounting directory
• local_dir is the directory or file from your host system (absolute path) that you want to access from inside your container. For example, the local_dir in the following path is /home/jsmith/data/mnist.-v /home/jsmith/data/mnist:/data/mnistIf you are inside the container, for example, ls /data/mnist, you will see the same files as if you issued the ls /home/jsmith/data/mnist command from outside the container.
• container_dir is the target directory when you are inside your container. For example, /data/mnist is the target directory in the example:-v /home/jsmith/data/mnist:/data/mnist
• <xx.xx> is the tag. For example, 17.06.

 

For any queries, raise a ticket in the helpdesk or please contact System Administrator, #103,SERC.