A short summary of PyTorch's methods for successful installation verification

I. Confirm the PyTorch version

After installing PyTorch, you can run the following code to confirm the version of PyTorch:

import torch
print(torch.__version__)

If no errors are reported and the correct version number is output, PyTorch has been successfully installed.

II. Testing PyTorch Basic Functionality

To ensure that the PyTorch base functionality is working properly, the following tests can be performed:

1. Test if you can create a tensor:

import torch
x = (5, 3)
print(x)

If no error is reported and a tensor with 5 rows and 3 columns is also output, it means that the tensor can be created.

2. Test if tensor calculation is possible:

import torch
x = (5, 3)
y = (3, 4)
z = (x, y)
print(z)

If no error is reported and a tensor of 5 rows and 4 columns is also output, the tensor calculation can be performed.

III. Testing PyTorch on GPUs

If your computer has GPU support, it is recommended to test PyTorch on the GPU to see if it works properly. The test code is as follows:

import torch
if .is_available():
    x = (5, 3).cuda()
    y = (3, 4).cuda()
    z = (x, y)
    print(z)

If no errors are reported and a tensor with 5 rows and 4 columns is also output, it means that the PyTorch GPU version is also working properly.

IV. Testing with sample code

To be more sure that PyTorch is working properly, you can test it with the official PyTorch example code, such as the following code:

import torch
import torchvision
model = .resnet18(pretrained=True)
()
x = (1, 3, 224, 224)
y = model(x)
print(y)

If no error is reported and the correct result is also output, it means that PyTorch is working properly.

V. Summary

These are just a few ways to verify that PyTorch is installed successfully. It is very important to confirm that PyTorch is working properly to avoid subsequent problems. If all the above tests fail, please read the PyTorch installation documentation carefully to troubleshoot the cause of the failure and ensure that PyTorch is installed correctly.

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