Deep Learning GPU PyTorch 1.11 Packaged by IOanyT Innovations - Ubuntu 20.04

OVERVIEW

PyTorch is an optimized tensor library for deep learning using GPUs and CPUs. PyTorch is an open source machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface.

PyTorch provides two high-level features:

• Tensor computing (like NumPy) with strong acceleration via graphics processing units (GPU)

• Deep neural networks built on a tape-based automatic differentiation system

Features classified by release status are as below:

Stable: These features will be maintained long-term and there should generally be no major performance limitations or gaps in documentation.

Beta: These features are tagged as Beta because the API may change based on user feedback, because the performance needs to improve, or because coverage across operators is not yet complete.

For Beta features, we are committing to seeing the feature through to the Stable classification. We are not, however, committing to backwards compatibility.

Prototype: These features are typically not available as part of binary distributions like PyPI or Conda, except sometimes behind run-time flags, and are at an early stage for feedback and testing.

GOALS

1. One-click launch

2. Easy configurable AMI with pre-installed Ubuntu 20.04 Server with Deep Learning GPU PyTorch 1.11

INSTALLATION VIA AWS MARKETPLACE

Kindly click on the below link to install the server via AWS Marketplace:

Pending...

GET STARTED

To verify the installation, follow the below instructions

Step 1. Connect to SSH

In a terminal window, use the ssh command to connect to the instance. You specify the user name for your instance, and the public DNS name or IPv6 address for your instance, the path and file name of the private key (.pem).

ssh ubuntu@publicIP -i [Path of key pair file]

If it shows access denied message run the following command , then run the above command again to connect via ssh.

chmod 400 [Path of key pair file]