How to create and manipulate tensors in PyTorch?

To create and manipulate tensors in PyTorch, you first need to import the torch library. Here are some commonly used methods for creating and manipulating tensors.

1. Create a tensor:

import torch

# 创建一个空的张量
empty_tensor = torch.Tensor()

# 创建一个包含随机数据的张量
random_tensor = torch.rand(2, 3)

# 创建一个全零的张量
zero_tensor = torch.zeros(2, 3)

# 创建一个全一的张量
ones_tensor = torch.ones(2, 3)

# 从Python列表创建张量
list_tensor = torch.tensor([1, 2, 3])

# 从Numpy数组创建张量
import numpy as np
numpy_array = np.array([1, 2, 3])
numpy_tensor = torch.from_numpy(numpy_array)

1. Tensor operations

# 张量的加法
tensor1 = torch.tensor([1, 2, 3])
tensor2 = torch.tensor([4, 5, 6])
result = tensor1 + tensor2

# 张量的乘法
result = tensor1 * tensor2

# 张量的索引和切片
tensor = torch.tensor([[1, 2, 3], [4, 5, 6]])
print(tensor[0, 1])  # 输出 2
print(tensor[:, 1])  # 输出 [2, 5]

# 张量的形状变换
tensor = torch.tensor([[1, 2], [3, 4]])
reshaped_tensor = tensor.view(1, 4)

# 张量的转置
tensor = torch.tensor([[1, 2], [3, 4]])
transposed_tensor = tensor.t()

# 张量的求和和平均值
tensor = torch.tensor([[1, 2], [3, 4]])
sum_tensor = torch.sum(tensor)
mean_tensor = torch.mean(tensor)

These are some common methods for creating and manipulating tensors, PyTorch also offers many other functions for handling tensors. Detailed documentation can be found on the official PyTorch website.