PyTorch on ARC: Difference between revisions
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= Installing PyTorch = | = Installing PyTorch = | ||
== Conda == | |||
You will need a working local '''conda''' install in your home directory first. | |||
If you do not have it yet, plaese follow [[Conda_on_ARC#Installing_Conda | these instructions]] | |||
to have it isntalled. | |||
== PyTorch == | |||
Revision as of 20:03, 31 January 2022
Intro to Torch
Checkpointing
Installing PyTorch
Conda
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.
PyTorch
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.")
# -------------------------------------------------------