Add utility tensor function

pygrad/tensor.py

@@ -1,8 +1,13 @@
 import numpy as np
 
+def tensor(*args, **kwargs):
+  return Tensor(*args, **kwargs)
+
 class Tensor:
   # TODO Implement 'requires_grad' functionality.
   def __init__(self, value):
+    # NOTE We technically could support both numpy arrays and scalar values,
+    # but it is too much work.
     if not isinstance(value, np.ndarray):
       print(f"{type(value)} is not compatible with {np.ndarray}")
       exit(-1)