add check that layers still have different dimensions

ml-agents/mlagents/trainers/tests/torch/saver/test_saver.py

     # asserts convolutions have different parameters before load
     for conv1, conv2 in zip(conv_params, conv_params2):
         assert not torch.equal(conv1, conv2)
+    # asserts layers still  have different dimensions
+    for mod1, mod2 in zip(policy.actor.parameters(), policy2.actor.parameters()):
+        if mod1.shape[0] == 12:
+            assert mod2.shape[0] == 10
+    # asserts layers still  have different dimensions
+    for mod1, mod2 in zip(policy.actor.parameters(), policy2.actor.parameters()):
+        if mod1.shape[0] == 12:
+            assert mod2.shape[0] == 10
 
 
 @pytest.mark.parametrize(