pytorch

pytorch is a Python package that provides two high-level features:

  • Tensor computation (like numpy) with strong GPU acceleration
  • Deep Neural Networks built on a tape-based autograd system

You can reuse your favorite Python packages such as numpy, scipy and Cython to extend pytourch when needed.

Running pytorch :

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. To run the container, choose interactive mode or non-interactive mode.a. Interactive mode: Open a command prompt and issue:

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

b. Non-interactive mode: Open a command prompt and issue:

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

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.
  • <command> is the command you want to run in the image.

 

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