test for SharedActorCritic

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

 import pytest
 
 from mlagents.torch_utils import torch
-from mlagents.trainers.torch.networks import NetworkBody, ValueNetwork, SimpleActor
+from mlagents.trainers.torch.networks import (
+    NetworkBody,
+    ValueNetwork,
+    SimpleActor,
+    SharedActorCritic,
+)
 from mlagents.trainers.settings import NetworkSettings
 from mlagents_envs.base_env import ActionSpec
 from mlagents.trainers.tests.dummy_config import create_observation_specs_with_shapes
             assert _out[0] == pytest.approx(1.0, abs=0.1)
 
 
+@pytest.mark.parametrize("shared", [True, False])
-def test_actor_critic(lstm):
+def test_actor_critic(lstm, shared):
     obs_size = 4
     network_settings = NetworkSettings(
         memory=NetworkSettings.MemorySettings() if lstm else None, normalize=True
     stream_names = [f"stream_name{n}" for n in range(4)]
     # action_spec = ActionSpec.create_continuous(act_size[0])
     action_spec = ActionSpec(act_size, tuple(act_size for _ in range(act_size)))
-    actor = SimpleActor(obs_spec, network_settings, action_spec)
-    critic = ValueNetwork(stream_names, obs_spec, network_settings)
+    if shared:
+        actor = critic = SharedActorCritic(
+            obs_spec, network_settings, action_spec, stream_names, network_settings
+        )
+    else:
+        actor = SimpleActor(obs_spec, network_settings, action_spec)
+        critic = ValueNetwork(stream_names, obs_spec, network_settings)
     if lstm:
         sample_obs = torch.ones((1, network_settings.memory.sequence_length, obs_size))
         memories = torch.ones(