PyTorch on ARC

Intro to Torch

Checkpointing

• https://pytorch.org/tutorials/recipes/recipes/saving_and_loading_a_general_checkpoint.html

Installing PyTorch

You will need a working local Conda install in your home directory first. If you do not have it yet, plaese follow these instructions to have it isntalled.

Once you have your own Conda, activate it with

$ ~/software/init-conda

We will install PyTorch into its own conda environment. It is very important to create the environment with python and pytorch in the same command. This way conda can select the best pytorch and python combination.

Test script

torch-gpu-test.py:

#! /usr/bin/env python 
# -------------------------------------------------------
import torch
# -------------------------------------------------------
print("Defining torch tensors:")
x = torch.Tensor(5, 3)
print(x)
y = torch.rand(5, 3)
print(y)

# -------------------------------------------------------
# let us run the following only if CUDA is available
if torch.cuda.is_available():
    print("CUDA is available.")
    x = x.cuda()
    y = y.cuda()
    print(x + y)
else:
    print("CUDA is NOT available.")

# -------------------------------------------------------