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This article mainly introduces the relevant knowledge of "how to use cpu to run code without gpu in python". The editor shows you the operation process through an actual case. The method of operation is simple and fast, and it is practical. I hope this article "how to change to cpu without gpu in python" can help you solve the problem.

Without gpu, use cpu to run the code instead.

Think that very troublesome changes, very aggressive changes, and endless error reports, as a result, changes to the code on the device OK, surprise, meaning no surprise!

That is to say,

Just set the device to the following to device=torch.device ("cuda:0" if torch.cuda.is_available () else "cpu"))

In addition, you don't need to set it all this way, just look at the source of the call to device where the error is reported, and modify the parentheses in torch.device ().

Tensorflow-gpu disable gpu setting (cpu versus gpu speed comparison) disable gpu setting # before import tensorflow import osos.environ ['CUDA_VISIBLE_DEVICES'] ='-1'cpu compares with gpu

Video card: GTX 1066

Cpu

Gpu

Simple test: gpu is 5 seconds faster than cpu

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