PyTorch get started

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Riguz留言 | 贡献2023年12月11日 (一) 04:38的版本 →‎Tensor(张量)

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)