torch.tensor

`torch.tensor`是PyTorch中创建张量（tensor）的函数，它可以将Python的list、tuple、NumPy的ndarray等数据类型转换为PyTorch中的张量。张量是PyTorch中最基本的数据类型，类似于Numpy中的多维数组，但它可以在GPU上运算并且支持自动求导。例如，可以使用以下代码创建一个3行2列的张量：

import torch

data = [[1, 2], [3, 4], [5, 6]]
tensor = torch.tensor(data)
print(tensor)

输出结果为：

tensor([[1, 2],
        [3, 4],
        [5, 6]])

相关问题

torch.Tensor

torch.Tensor is a multi-dimensional array used in PyTorch, a popular open-source machine learning framework. It is similar to the numpy array, but with additional support for GPU acceleration and automatic differentiation.

The torch.Tensor object can be created using a list or a numpy array and can be manipulated using various operations such as addition, subtraction, multiplication, and division. Additionally, it can be indexed and sliced just like a numpy array.

The tensor can also be moved to a GPU device using the `.to()` method, which allows for faster computation. The tensor can be converted to a numpy array using the `.numpy()` method.

Overall, torch.Tensor is a fundamental data structure in PyTorch and is used extensively in deep learning for storing and manipulating data.