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VOOZH | about |
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VOOZH | about |
By Nouman and Shaoni Mukherjee
Thanks for learning with the DigitalOcean Community. Check out our offerings for compute, storage, networking, and managed databases.
With a strong background in data science and over six years of experience, I am passionate about creating in-depth content on technologies. Currently focused on AI, machine learning, and GPU computing, working on topics ranging from deep learning frameworks to optimizing GPU-based workloads.
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If using GPU, the model needs to be moved to the device, otherwise the training will fail because the model will stay on CPU while the images are labels are later on move to the GPU device (images.to(device), labels.to(device)):
model = ConvNeuralNet(num_classes) model = model.to(device) # Add this line to move model to GPU/CPU
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