operations unit tests

norch/utils/__init__.py

@@ -0,0 +1 @@
+from .utils import *

norch/utils/utils.py

@@ -1,5 +1,5 @@
 import random
-import numpy as np
+import torch
 
 
 def generate_random_list(shape):
@@ -14,4 +14,27 @@ def generate_random_list(shape):
             return [random.uniform(-1, 1) for _ in range(shape[0])]
         else:
             return [generate_random_list(inner_shape) for _ in range(shape[0])]
-        
+        
+
+def to_torch(custom_tensor):
+    shape = custom_tensor.shape
+    pytorch_tensor = torch.zeros(shape)
+    
+    def _iterate_indices(shape):
+        if len(shape) == 0:
+            yield ()
+        else:
+            for index in range(shape[0]):
+                for sub_indices in _iterate_indices(shape[1:]):
+                    yield (index,) + sub_indices
+    
+    # Iterate over all elements using the custom tensor's __getitem__ method
+    for indices in _iterate_indices(shape):
+        value = custom_tensor[indices]
+        pytorch_tensor[tuple(indices)] = value
+    
+    return pytorch_tensor
+
+def compare_torch(tensor1, tensor2, epsilon=1e-5):
+    diff = torch.abs(tensor1 - tensor2)    
+    return torch.all(diff < epsilon)