查看“︁PyTorch get started”︁的源代码

= Installation =
== Conda Installation== 

<syntaxhighlight lang="bash">
conda create --name deeplearning python=3.11
conda activate deeplearning
python --version
// 3.11.5
</syntaxhighlight>

== Install pytorch ==

<syntaxhighlight lang="bash">
conda install pytorch::pytorch torchvision torchaudio -c pytorch
</syntaxhighlight>

To verify:

<syntaxhighlight lang="python">
import torch
x = torch.rand(5, 3)
print(x)
</syntaxhighlight>

Output:
<syntaxhighlight lang="bash">
tensor([[0.2162, 0.2653, 0.6725],
        [0.5371, 0.4180, 0.1353],
        [0.3697, 0.5238, 0.0332],
        [0.6179, 0.5008, 0.9435],
        [0.1182, 0.3233, 0.9071]])
</syntaxhighlight>

= Concepts =
== Tensor ==
Tensors are a specialized data structure that are very similar to arrays and matrices. In PyTorch, we use tensors to encode the inputs and outputs of a model, as well as the model’s parameters.

Tensors are similar to NumPy’s ndarrays, except that tensors can run on GPUs or other hardware accelerators.


[[Category:Deep Learning]]
[[Category:PyTorch]]