Fix LSTM tests

ml-agents/mlagents/trainers/tests/torch/test_networks.py

     obs_size = 4
     seq_len = 16
     network_settings = NetworkSettings(
-        memory=NetworkSettings.MemorySettings(sequence_length=seq_len, memory_size=4)
+        memory=NetworkSettings.MemorySettings(sequence_length=seq_len, memory_size=12)
-    optimizer = torch.optim.Adam(networkbody.parameters(), lr=3e-3)
+    optimizer = torch.optim.Adam(networkbody.parameters(), lr=3e-4)
-    for _ in range(100):
-        encoded, _ = networkbody([sample_obs], [], memories=torch.ones(1, seq_len, 4))
+    for _ in range(200):
+        encoded, _ = networkbody([sample_obs], [], memories=torch.ones(1, seq_len, 12))
         # Try to force output to 1
         loss = torch.nn.functional.mse_loss(encoded, torch.ones(encoded.shape))
         optimizer.zero_grad()
         # memories isn't always set to None, the network should be able to
         # deal with that.
     # Test critic pass
-    value_out = actor.critic_pass([sample_obs], [], memories=memories)
+    value_out, memories_out = actor.critic_pass([sample_obs], [], memories=memories)
+            assert memories_out.shape == memories.shape
         else:
             assert value_out[stream].shape == (1,)