1import torch 

2from fastai.data.block import TransformBlock 

3import numpy as np 

4 

5def bool_to_tensor(value: bool): 

6 return torch.FloatTensor(value) 

7 

8 

9def unsqueeze(inputs): 

10 """This is needed to transform the input with an extra dimension added to the end of the tensor.""" 

11 return inputs.unsqueeze(dim=-1).float() 

12 

13 

14def BoolBlock(**kwargs): 

15 return TransformBlock( 

16 item_tfms=[bool_to_tensor], 

17 batch_tfms=unsqueeze, 

18 **kwargs 

19 ) 

20 

21 

22def float64_to_32(value: np.float64): 

23 return np.float32(value) 

24 

25 

26def Float32Block(**kwargs): 

27 return TransformBlock( 

28 item_tfms=[float64_to_32], 

29 **kwargs 

30 )