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DPS921/PyTorch: Convolutional Neural Networks

2 bytes added, 13:18, 30 November 2020
Parallelization Methods
Here is a toy model that contains two linear layers. Each linear layer is designed to run a separate GPU.
 
import torch
x = self.relu(self.net1(x.to('cuda:0')))
return self.net2(x.to('cuda:1'))
 
The code is very similar to a single GPU implementation, except for the ''.to('cuda:x')'' calls, where ''cuda:0'' and ''cuda:1'' are each their own GPU.
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