making masked actions impossible instead of improbable

ml-agents/mlagents/trainers/models.py

         action_idx = [0] + list(np.cumsum(action_size))
         branches_logits = [all_logits[:, action_idx[i]:action_idx[i + 1]] for i in range(len(action_size))]
         branch_masks = [action_masks[:, action_idx[i]:action_idx[i + 1]] for i in range(len(action_size))]
-        raw_probs = [tf.multiply(tf.nn.softmax(branches_logits[k]), branch_masks[k]) + 1.0e-10
+        raw_probs = [tf.multiply(tf.nn.softmax(branches_logits[k]) + 1.0e-10, branch_masks[k])
-            tf.divide(raw_probs[k], tf.reduce_sum(raw_probs[k] + 1.0e-10, axis=1, keepdims=True))
-                            for k in range(len(action_size))]
+            tf.divide(raw_probs[k], tf.reduce_sum(raw_probs[k], axis=1, keepdims=True))
+            for k in range(len(action_size))]
-        return output, tf.concat([tf.log(normalized_probs[k]) for k in range(len(action_size))], axis=1)
+        return output, tf.concat([tf.log(normalized_probs[k] + 1.0e-10) for k in range(len(action_size))], axis=1)
 
     def create_observation_streams(self, num_streams, h_size, num_layers):
         """