PyTorch get started
Installation
Conda Installation
conda create --name deeplearning python=3.11
conda activate deeplearning
python --version
// 3.11.5
Install pytorch
conda install pytorch::pytorch torchvision torchaudio -c pytorch
To verify:
import torch
x = torch.rand(5, 3)
print(x)
Output:
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]])
Concepts
Tensor(张量)
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
- tensors are also optimized for automatic differentiation(自动微分)