amend

pytorch · Feb 12, 2024 · c8de01b · c8de01b
1 parent f095c01
commit c8de01b
Showing 1 changed file with 16 additions and 1 deletion.
diff --git a/test/test_cost.py b/test/test_cost.py
@@ -8863,6 +8863,9 @@ def test_iql_batcher(
             loss_ms = loss_fn(ms_td)
         assert loss_fn.tensor_keys.priority in ms_td.keys()
 
+        # Remove warnings
+        SoftUpdate(loss_fn, eps=0.5)
+
         with torch.no_grad():
             torch.manual_seed(0)  # log-prob is computed with a random action
             np.random.seed(0)
@@ -9286,6 +9289,7 @@ def test_discrete_iql(
             temperature=temperature,
             expectile=expectile,
             loss_function="l2",
+            action_space="one-hot",
         )
         if td_est in (ValueEstimators.GAE, ValueEstimators.VTrace):
             with pytest.raises(NotImplementedError):
@@ -9408,6 +9412,7 @@ def test_discrete_iql_state_dict(
             temperature=temperature,
             expectile=expectile,
             loss_function="l2",
+            action_space="one-hot",
         )
         sd = loss_fn.state_dict()
         loss_fn2 = DiscreteIQLLoss(
@@ -9418,6 +9423,7 @@ def test_discrete_iql_state_dict(
             temperature=temperature,
             expectile=expectile,
             loss_function="l2",
+            action_space="one-hot",
         )
         loss_fn2.load_state_dict(sd)
 
@@ -9431,6 +9437,7 @@ def test_discrete_iql_separate_losses(self, separate_losses):
             value_network=value,
             loss_function="l2",
             separate_losses=separate_losses,
+            action_space="one-hot",
         )
         with pytest.warns(UserWarning, match="No target network updater has been"):
             loss = loss_fn(td)
@@ -9609,6 +9616,7 @@ def test_discrete_iql_batcher(
             temperature=temperature,
             expectile=expectile,
             loss_function="l2",
+            action_space="one-hot",
         )
 
         ms = MultiStep(gamma=gamma, n_steps=n).to(device)
@@ -9624,6 +9632,8 @@ def test_discrete_iql_batcher(
             loss_ms = loss_fn(ms_td)
         assert loss_fn.tensor_keys.priority in ms_td.keys()
 
+        SoftUpdate(loss_fn, eps=0.5)
+
         with torch.no_grad():
             torch.manual_seed(0)  # log-prob is computed with a random action
             np.random.seed(0)
@@ -9695,6 +9705,7 @@ def test_discrete_iql_tensordict_keys(self, td_est):
             qvalue_network=qvalue,
             value_network=value,
             loss_function="l2",
+            action_space="one-hot",
         )
 
         default_keys = {
@@ -9720,6 +9731,7 @@ def test_discrete_iql_tensordict_keys(self, td_est):
             qvalue_network=qvalue,
             value_network=value,
             loss_function="l2",
+            action_space="one-hot",
         )
 
         key_mapping = {
@@ -9755,7 +9767,10 @@ def test_discrete_iql_notensordict(
         value = self._create_mock_value(observation_key=observation_key)
 
         loss = DiscreteIQLLoss(
-            actor_network=actor, qvalue_network=qvalue, value_network=value
+            actor_network=actor,
+            qvalue_network=qvalue,
+            value_network=value,
+            action_space="one-hot",
         )
         loss.set_keys(
             action=action_key,