diff --git a/nemo_rl/models/policy/dtensor_policy_worker.py b/nemo_rl/models/policy/dtensor_policy_worker.py
index 39119f2381..cc12939d46 100644
--- a/nemo_rl/models/policy/dtensor_policy_worker.py
+++ b/nemo_rl/models/policy/dtensor_policy_worker.py
@@ -222,10 +222,9 @@ def __init__(
             f"World size({world_size}) must equal to dp_size({dp_size}) * tp_size({tp_size}) * cp_size({cp_size}) to use DTensor"
         )
 
-        if sequence_parallel_enabled:
-            assert tp_size > 1, (
-                "Sequence parallel needs to be used together with tensor parallel. "
-                "Please either set tp_size > 1 or disable sequence parallel."
+        if sequence_parallel_enabled and tp_size == 1:
+            print(
+                "[WARNING]: sequence_parallel=True, but tp_size=1 which has no effect. Enable tp_size > 1 to use sequence parallelism."
             )
 
         if cp_size > 1:
diff --git a/tests/unit/models/policy/test_dtensor_worker.py b/tests/unit/models/policy/test_dtensor_worker.py
index e208873353..fcd0977117 100644
--- a/tests/unit/models/policy/test_dtensor_worker.py
+++ b/tests/unit/models/policy/test_dtensor_worker.py
@@ -42,7 +42,7 @@ def create_test_config(
     sequence_parallel: bool = False,
     cpu_offload: bool = False,
     activation_checkpointing: bool = False,
-    custom_parallel_plan: str = None,
+    custom_parallel_plan: str | None = None,
 ) -> PolicyConfig:
     return {
         "model_name": model_name,
@@ -237,7 +237,7 @@ def test_lm_policy_init(policy_setup):
 @pytest.fixture
 def training_setup(request, two_gpu_virtual_cluster):
     """Setup and teardown specifically for training tests."""
-    model_name, tp, cp, cpu_offload, sequence_parallel, activation_checkpointing = (
+    model_name, tp, cp, sequence_parallel, cpu_offload, activation_checkpointing = (
         request.param
     )
     policy = None
@@ -246,7 +246,7 @@ def training_setup(request, two_gpu_virtual_cluster):
 
     try:
         config = create_test_config(
-            model_name, tp, cp, cpu_offload, sequence_parallel, activation_checkpointing
+            model_name, tp, cp, sequence_parallel, cpu_offload, activation_checkpointing
         )
         tokenizer = get_tokenizer(config["tokenizer"])
         print(
@@ -300,8 +300,7 @@ def training_setup(request, two_gpu_virtual_cluster):
 @pytest.mark.parametrize(
     "training_setup",
     [
-        # model_name, tp, cp, cpu_offload, sequence_parallel, activation_checkpointing
-        # Split grid over tp/cp/cpu/sp/act across qwen and llama
+        # model_name                        tp cp  sp     cpu    act
         (TEST_ASSETS.TINY_LLAMA_MODEL_PATH, 1, 1, False, False, False),
         (TEST_ASSETS.TINY_LLAMA_MODEL_PATH, 1, 1, True, False, False),
         (TEST_ASSETS.TINY_LLAMA_MODEL_PATH, 1, 1, False, True, False),
@@ -317,7 +316,14 @@ def training_setup(request, two_gpu_virtual_cluster):
         (TEST_ASSETS.TINY_QWEN3_MODEL_PATH, 1, 1, False, True, True),
         (TEST_ASSETS.TINY_QWEN3_MODEL_PATH, 1, 1, True, True, True),
         (TEST_ASSETS.TINY_QWEN3_MODEL_PATH, 1, 2, False, False, False),
-        (TEST_ASSETS.TINY_GEMMA3_MODEL_PATH, 1, 1, True, True, False),
+        (
+            TEST_ASSETS.TINY_GEMMA3_MODEL_PATH,
+            1,
+            1,
+            True,
+            True,
+            False,
+        ),  # gemma3 doesn't support spda
         (TEST_ASSETS.TINY_GEMMA3_MODEL_PATH, 1, 1, True, False, True),
         (TEST_ASSETS.TINY_GEMMA3_MODEL_PATH, 1, 1, False, True, True),
         (TEST_ASSETS.TINY_GEMMA3_MODEL_PATH, 1, 1, True, True, True),
@@ -363,7 +369,7 @@ def verify_loss_tensor(loss_tensor):
 @pytest.fixture
 def logprob_setup(request, two_gpu_virtual_cluster):
     """Setup and teardown specifically for training tests."""
-    model_name, tp, cp, cpu_offload, sequence_parallel, activation_checkpointing = (
+    model_name, tp, cp, sequence_parallel, cpu_offload, activation_checkpointing = (
         request.param
     )
     policy = None
@@ -371,7 +377,7 @@ def logprob_setup(request, two_gpu_virtual_cluster):
 
     try:
         config = create_test_config(
-            model_name, tp, cp, cpu_offload, sequence_parallel, activation_checkpointing
+            model_name, tp, cp, sequence_parallel, cpu_offload, activation_checkpointing
         )
         tokenizer = get_tokenizer(config["tokenizer"])
         print(
@@ -494,8 +500,9 @@ def test_dtensor_tp_and_tied_model_with_custom_parallel_plan(two_gpu_virtual_clu
     config = create_test_config(
         model_name=TEST_ASSETS.TINY_LLAMA_TIED_MODEL_PATH,
         tp=2,
-        cpu_offload=False,
+        cp=1,
         sequence_parallel=False,
+        cpu_offload=False,
         activation_checkpointing=False,
         custom_parallel_plan=custom_parallel_plan,
     )