The rank of a tensor signifies the number of dimensions present within the tensor. We can use the following code to get the rank of a tensor:

`torch.linalg.matrix_rank(my_tensor)`

Complete code:

```
import torch
my_data = [[0.1051, 0.0710],
[0.5582, 0.7901],
[0.2262, 0.2459]]
my_tensor = torch.Tensor(my_data)
rank_tensor = torch.linalg.matrix_rank(my_tensor)
print("Rank of tensor: ", rank_tensor)
```

Output:

`Rank of tensor: tensor(2)`

Above, the tensor in the example is of rank 2.