Coverage for NeuralTSNE/NeuralTSNE/Utils/Loaders/LabelLoaders/label_loaders.py: 100%

1import io 

2from typing import Union 

3 

4import numpy as np 

5import torch 

6 

7 

8def load_labels(labels: io.TextIOWrapper) -> Union[torch.Tensor, None]: 

9 """ 

10 Load labels from a text file into a `torch.Tensor`. 

11 

12 The function reads labels from the provided text file and converts them into a `torch.Tensor` of type `float`. 

13 If the `labels` parameter is not provided or the file is empty, the function returns `None`. 

14 

15 Parameters 

16 ---------- 

17 `labels` : `io.TextIOWrapper` 

18 The `file` object containing labels to be loaded. 

19 

20 Returns 

21 ------- 

22 `torch.Tensor` | `None` 

23 A `torch.Tensor` containing loaded labels or `None` if no labels are available. 

24 

25 Note 

26 ---- 

27 - The function expects the `labels` parameter to be a file object (`io.TextIOWrapper`) with labels in text format. 

28 - If the file is not provided or is empty, the function returns `None`. 

29 - The labels are read from the file using `numpy` and then converted to a `torch.Tensor` of type `float`. 

30 """ 

31 read_labels = None 

32 if labels: 

33 read_labels = np.loadtxt(labels) 

34 read_labels = torch.from_numpy(read_labels).float() 

35 labels.close() 

36 return read_labels