Jerome Paliakkara jerome9189

## cifar10_gpu.py
import torch
import torchvision
import torchvision.transforms as transforms


transform = transforms.Compose(
    [transforms.ToTensor(),
     transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])

batch_size = 4

## computing_infrastructure.md

      
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                — forked from ZhaofengWu/computing_infrastructure.md
            
              
                CSE 447/517 Winter 2022 Computing Infrastructure
              
          
    CSE 447/517 Winter 2022 Computing Infrastructure

Welcome to CSE 447/517 Natural Language Processing! This document gives an overview of the computing resources available to you for this course and some development recommendations. If you have more questions, feel free to ask them on Ed!
Resources

We have a variety of resources for this course, including GPUs. Of course, you can always your own laptop/machine, but it is not recommended since (a) many things that we do will be quite expensive; (b) some libraries may not have good non-linux support; and (c) you probably do not want large datasets/models/etc. to occupy all your disk space. See the next section for tips that will make remote development smooth.
CSE Machines
	import torch
	import torchvision
	import torchvision.transforms as transforms


	transform = transforms.Compose(
	[transforms.ToTensor(),
	transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])

	batch_size = 4