diff --git a/python/sglang/kernels/jit/csrc/speculative/tree.cuh b/python/sglang/kernels/jit/csrc/speculative/tree.cuh
index 70d3ccbd4..66a6bd6b5 100644
--- a/python/sglang/kernels/jit/csrc/speculative/tree.cuh
+++ b/python/sglang/kernels/jit/csrc/speculative/tree.cuh
@@ -48,7 +48,7 @@ inline void build_tree_kernel_efficient(
   TensorMatcher({batch_size, parent_width})
       .with_strides({parent_list.size(1) == 0 ? -1 : parent_list.size(1), 1})
       .with_dtype<int64_t>()
-      .with_device<kDLCUDA>(device)
+      .with_device<kDLGPU>(device)
       .verify(parent_list);
   CHECK_HOST(depth == 1 || parent_width.unwrap() == topk * (depth - 1) + 1);
   TensorMatcher({batch_size, draft_token_num - 1})
@@ -138,7 +138,7 @@ inline void verify_tree_greedy(
   SymbolicDevice device;
   TensorMatcher({batch_size, draft_tokens})
       .with_dtype<int64_t>()
-      .with_device<kDLCUDA>(device)
+      .with_device<kDLGPU>(device)
       .verify(candidates)
       .verify(retrive_index)
       .verify(retrive_next_token)
@@ -183,7 +183,7 @@ inline void reconstruct_indices_from_tree_mask(
   // Bytes, not element type -- same reasoning as build_tree_kernel_efficient:
   // the kernel casts straight to bool* and callers are free to spell a 1-byte
   // mask as bool or uint8.
-  TensorMatcher({-1}).with_device<kDLCUDA>(device).verify(tree_mask);
+  TensorMatcher({-1}).with_device<kDLGPU>(device).verify(tree_mask);
   CHECK_HOST(tree_mask.dtype().bits == 8);
   CHECK_HOST(tree_mask.numel() >= batch_size * draft_token_num * draft_token_num);
   TensorMatcher({batch_size}).with_dtype<int64_t>().with_device(device).verify(verified_seq_len);
diff --git a/test/registered/kernels/ops/attention/test_q8kv8_sparse_prefill_backend.py b/test/registered/kernels/ops/attention/test_q8kv8_sparse_prefill_backend.py
index 9080914ba..57d061339 100644
--- a/test/registered/kernels/ops/attention/test_q8kv8_sparse_prefill_backend.py
+++ b/test/registered/kernels/ops/attention/test_q8kv8_sparse_prefill_backend.py
@@ -78,7 +78,7 @@ class _TokenToKVPool:
             extra_key_buffer if extra_key_buffer is not None else swa_key_buffer
         )
         self.full_to_swa_index_mapping = full_to_swa_index_mapping
-        self.swa_page_size = page_size
+        self.swa_kv_pool = _Pool(page_size)
 
     def get_swa_key_buffer_radix(self, layer_id: int) -> torch.Tensor:
         _ = layer_id
@@ -86,7 +86,7 @@ class _TokenToKVPool:
 
     def get_extra_key_page_size(self, layer_id: int) -> int:
         _ = layer_id
-        return self.swa_page_size
+        return self.swa_kv_pool.page_size
 
     def get_extra_key_buffer(self, layer_id: int) -> torch.Tensor:
         _ = layer_id
diff --git a/test/registered/unit/hardware_backend/mlx/test_metal_profiler.py b/test/registered/unit/hardware_backend/mlx/test_metal_profiler.py
index 2e38e67ba..b9feaec83 100644
--- a/test/registered/unit/hardware_backend/mlx/test_metal_profiler.py
+++ b/test/registered/unit/hardware_backend/mlx/test_metal_profiler.py
@@ -20,6 +20,7 @@ import unittest
 from pathlib import Path
 from unittest.mock import MagicMock, patch
 
+from sglang.srt.runtime_context import get_parallel
 from sglang.test.ci.ci_register import register_mlx_ci
 
 register_mlx_ci(est_time=5, suite="stage-a-unit-test-mlx")
@@ -267,6 +268,7 @@ class TestSchedulerProfilerManagerMPS(unittest.TestCase):
                     torch.mps.profiler, "metal_capture", return_value=capture_ctx
                 ),
                 mock_patch("torch.distributed.barrier"),
+                get_parallel().override(tp_rank=0, pp_size=1, moe_ep_size=1),
             ):
                 result = mgr._start_profile()
                 self.assertTrue(result.success, result.message)
diff --git a/test/registered/unit/managers/test_disagg_idle_step_counters.py b/test/registered/unit/managers/test_disagg_idle_step_counters.py
index 781f3b0db..140d0f379 100644
--- a/test/registered/unit/managers/test_disagg_idle_step_counters.py
+++ b/test/registered/unit/managers/test_disagg_idle_step_counters.py
@@ -16,6 +16,7 @@ from sglang.srt.managers.schedule_batch import ScheduleBatch
 from sglang.srt.managers.scheduler import Scheduler
 from sglang.srt.managers.utils import GenerationBatchResult
 from sglang.srt.model_executor.forward_batch_info import ForwardMode
+from sglang.srt.runtime_context import get_parallel
 from sglang.srt.speculative.spec_info import SpeculativeAlgorithm
 from sglang.test.ci.ci_register import register_cpu_ci
 from sglang.test.test_utils import CustomTestCase
@@ -120,12 +121,11 @@ class TestSchedulerIdleStepCounters(CustomTestCase):
                                 scheduler.disagg_decode_transfer_queue.queue = [
                                     object()
                                 ]
-                        parallel = SimpleNamespace(
-                            pp_async_batch_depth=depth,
-                            enable_dsa_prefill_context_parallel=False,
-                        )
                         with (
-                            patch(f"{PP_MODULE}.get_parallel", return_value=parallel),
+                            get_parallel().override(
+                                pp_size=2,
+                                pp_async_batch_depth=depth,
+                            ),
                             patch(
                                 f"{PP_MODULE}.get_disagg",
                                 return_value=SimpleNamespace(
@@ -278,7 +278,10 @@ class TestSchedulerIdleStepCounters(CustomTestCase):
 
         scheduler.run_batch = run_batch
         scheduler.process_batch_result = process_batch_result
-        with self.assertRaises(StopIteration):
+        with (
+            get_parallel().override(pp_rank=0, attn_tp_rank=0, attn_cp_rank=0),
+            self.assertRaises(StopIteration),
+        ):
             event_loop(scheduler)
 
         self.assertEqual(observed_idle_flags, [False, False, after_idle, False])