updated basic tutorials, better comments, code revision, checked it works with latest pytorch version

ML/Pytorch/Basics/pytorch_tensorbasics.py

@@ -13,10 +13,11 @@ numpy array and vice-versa.
 
 Programmed by Aladdin Persson
 * 2020-06-27: Initial coding
-
+* 2022-12-19: Small revision of code, checked that it works with latest PyTorch version
 """
 
 import torch
+import numpy as np
 
 # ================================================================= #
 #                        Initializing Tensor                        #
@@ -77,8 +78,6 @@ print(
 print(f"Converted float64 {tensor.double()}")  # Converted to float64
 
 # Array to Tensor conversion and vice-versa
-import numpy as np
-
 np_array = np.zeros((5, 5))
 tensor = torch.from_numpy(np_array)
 np_array_again = (
@@ -112,7 +111,7 @@ t += x  # Also inplace: t = t + x is not inplace, bit confusing.
 
 # -- Exponentiation (Element wise if vector or matrices) --
 z = x.pow(2)  # z = [1, 4, 9]
-z = x ** 2  # z = [1, 4, 9]
+z = x**2  # z = [1, 4, 9]
 
 
 # -- Simple Comparison --
@@ -153,7 +152,7 @@ z = (
     x1 - x2
 )  # Shape of z is 5x5: How? The 1x5 vector (x2) is subtracted for each row in the 5x5 (x1)
 z = (
-    x1 ** x2
+    x1**x2
 )  # Shape of z is 5x5: How? Broadcasting! Element wise exponentiation for every row
 
 # Other useful tensor operations