refactor(tests): remove grpc import checks from test files for cleaner code

tests/policies/test_gaussian_actor_policy.py

@@ -15,9 +15,6 @@
 # limitations under the License.
 
 import pytest
-
-pytest.importorskip("grpc")
-
 import torch
 from torch import Tensor, nn
 
@@ -240,7 +237,7 @@ def test_gaussian_actor_policy_forward(batch_size: int, state_dim: int, action_d
 
 
 @pytest.mark.parametrize("batch_size,state_dim,action_dim", [(2, 6, 6), (1, 10, 10)])
-def test_sac_training_through_algorithm(batch_size: int, state_dim: int, action_dim: int):
+def test_gaussian_actor_training_through_sac(batch_size: int, state_dim: int, action_dim: int):
     config = create_default_config(state_dim=state_dim, continuous_action_dim=action_dim)
     algorithm, policy = _make_algorithm(config)
 
@@ -270,7 +267,7 @@ def test_sac_training_through_algorithm(batch_size: int, state_dim: int, action_
 
 
 @pytest.mark.parametrize("batch_size,state_dim,action_dim", [(2, 6, 6), (1, 10, 10)])
-def test_sac_training_with_visual_input(batch_size: int, state_dim: int, action_dim: int):
+def test_gaussian_actor_training_with_visual_input(batch_size: int, state_dim: int, action_dim: int):
     config = create_config_with_visual_input(state_dim=state_dim, continuous_action_dim=action_dim)
     algorithm, policy = _make_algorithm(config)
 
@@ -331,7 +328,7 @@ def test_gaussian_actor_policy_with_pretrained_encoder(
     assert actor_loss.shape == ()
 
 
-def test_sac_training_with_shared_encoder():
+def test_gaussian_actor_training_with_shared_encoder():
     batch_size = 2
     action_dim = 10
     state_dim = 10
@@ -358,7 +355,7 @@ def test_sac_training_with_shared_encoder():
     algorithm.optimizers["actor"].step()
 
 
-def test_sac_training_with_discrete_critic():
+def test_gaussian_actor_training_with_discrete_critic():
     batch_size = 2
     continuous_action_dim = 9
     full_action_dim = continuous_action_dim + 1
@@ -475,7 +472,7 @@ def test_sac_algorithm_with_critics_number_of_heads(num_critics: int):
 
 def test_gaussian_actor_policy_save_and_load(tmp_path):
     """Test that the policy can be saved and loaded from pretrained."""
-    root = tmp_path / "test_sac_save_and_load"
+    root = tmp_path / "test_gaussian_actor_save_and_load"
 
     state_dim = 10
     action_dim = 10
@@ -506,7 +503,7 @@ def test_gaussian_actor_policy_save_and_load(tmp_path):
 
 def test_gaussian_actor_policy_save_and_load_with_discrete_critic(tmp_path):
     """Discrete critic should be saved/loaded as part of the policy."""
-    root = tmp_path / "test_sac_save_and_load_discrete"
+    root = tmp_path / "test_gaussian_actor_save_and_load_discrete"
 
     state_dim = 10
     action_dim = 6