How to use the aten module in PyTorch?

The aten module in PyTorch is the underlying C++ implementation of PyTorch, providing many basic tensor operations and functions. Typically, we don’t need to directly use the aten module but instead use PyTorch’s high-level interface for model building and training. However, if you are interested in low-level operations, you can use the aten module in the following way:

1. ate

import torch.aten as aten

1. aten
2. Include aten.

import torch.aten as aten

# 创建两个张量
a = aten.tensor([1, 2, 3])
b = aten.tensor([4, 5, 6])

# 相加
c = aten.add(a, b)
print(c)  # 输出: tensor([5, 7, 9])

It is important to note that the functions and operations of the aten module are similar to PyTorch’s tensor operations, but their syntax and usage may be different. Therefore, if you want to delve deeper into the aten module, it is recommended to refer to PyTorch’s official documentation and source code.