torch.BoolTensor
时间: 2023-12-02 10:15:33 浏览: 22
torch.BoolTensor is a tensor that consists of elements of the boolean data type. Each element in the tensor can either be True or False. This tensor is useful for performing logical operations, such as AND, OR, and NOT, on binary data. It is a subclass of the torch.Tensor class and inherits all of its methods and attributes. The main difference between BoolTensor and other tensor types is that it only requires one bit to represent each element, rather than 8 bits (1 byte) for each element in a ByteTensor or 32 bits (4 bytes) for each element in a FloatTensor. This makes BoolTensor more memory-efficient for storing large arrays of binary data.
相关问题
torch.booltensor
torch.booltensor是用于创建一个布尔类型的张量的函数。它接受一个可迭代对象作为输入,并将其转换为布尔类型的张量。例如,你可以使用以下代码创建一个包含布尔值的张量:
```
import torch
data = [True, False, True, True]
bool_tensor = torch.BoolTensor(data)
print(bool_tensor)
```
输出将是:
```
tensor([ True, False, True, True])
```
注意:在最新的PyTorch版本中,`torch.BoolTensor()`已经被弃用,推荐使用`torch.tensor()`并指定dtype参数为`torch.bool`来创建布尔类型的张量。
torch中获取一个一维BoolTensor中所有True的位置
可以使用torch.nonzero()函数来获取一个一维BoolTensor中所有True的位置,示例如下:
```python
import torch
x = torch.BoolTensor([True, False, True, True, False])
indices = torch.nonzero(x)
print(indices)
```
输出结果为:
```
tensor([[0],
[2],
[3]])
```
其中,`indices`就是一个二维的tensor,表示所有True的位置。