Resolved log(0) error in KL divergence Issue#12233

machine_learning/loss_functions.py

@@ -659,7 +659,13 @@
     if len(y_true) != len(y_pred):
         raise ValueError("Input arrays must have the same length.")
 
-    kl_loss = y_true * np.log(y_true / y_pred)
+    kl_loss = np.concatenate(
+        (y_true[None, :], y_pred[None, :])
+    )  # true probs in first row and predicted in second
+    kl_loss = kl_loss[
+        :, np.any(kl_loss == 0, axis=0) == False
+    ]  # Filtered zero probabilities from both probability arrays
+    kl_loss = kl_loss[0] * np.log(kl_loss[0] / kl_loss[1])  # Calculating safely now
     return np.sum(kl_loss)