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时间: 2024-01-13 15:03:33 浏览: 26
`torch.arange` is a function in PyTorch used to create a one-dimensional tensor, where the elements increase by a fixed step size from a starting position up to a specified end position. The syntax is as follows:
```python
torch.arange(start=0, end, step=1, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) -> Tensor
```
Here, `start` represents the starting position (default is 0), `end` represents the end position (exclusive), and `step` represents the step size (default is 1). If `out` is not specified, a new tensor is created. `dtype` represents the data type of the output tensor (default is float32). `layout` represents the memory layout of the output tensor (default is `strided`). `device` represents the device of the output tensor (default is CPU). `requires_grad` represents whether or not gradients need to be computed (default is False).
For example, the following code creates a tensor that starts at 0, increments by 2, and stops before 10:
```python
import torch
a = torch.arange(0, 10, 2)
print(a)
```
The output is:
```
tensor([0, 2, 4, 6, 8])
```