implement transformer between numpy and torch format

mu_map/dataset/transform.py

 import math
 from typing import List, Tuple
 
+import numpy as np
 import torch
 from torch import Tensor
 
@@ -126,6 +127,20 @@ class PadCropTranform(SequenceTransform):
         )
 
 
+class ToNumpy():
+    """
+    Special transformer that converts torch tensors to numpy array.
+    """
+    def __call__(self, *tensors: Tensor) -> Tuple[np.ndarray, ...]:
+        return tuple(map(lambda tensor: tensor.numpy(), tensors))
+
+class ToTensor():
+    """
+    Special transformer that converts numpy arrays to torch tensors.
+    """
+    def __call__(self, *tensors: np.ndarray) -> Tuple[Tensor, ...]:
+        return tuple(map(lambda tensor: torch.from_numpy(tensor), tensors))
+
 if __name__ == "__main__":
     transform = PadCropTranform(dim=3, size=32)