[Nightly CI] Remove TP case (#3534)

Signed-off-by: NumberWan <wantszkin2003@gmail.com>

tests/e2e/online_serving/test_bagel_expansion.py

@@ -6,7 +6,6 @@ Coverage:
 - TeaCache
 - Cache-DiT
 - CFG-Parallel
-- Tensor-Parallel
 - Ulysses-SP
 - Ring-Attention
 - Layerwise Offloading
@@ -15,62 +14,23 @@ assert_diffusion_response validates successful generation and the expected
 512x512 resolution.
 """
 
-import json
-
 import pytest
 
 from tests.helpers.mark import hardware_marks
 from tests.helpers.runtime import OmniServer, OmniServerParams, OpenAIClientHandler, dummy_messages_from_mix_data
-from tests.helpers.stage_config import get_deploy_config_path
 
 pytestmark = [pytest.mark.diffusion, pytest.mark.full_model]
 
-_BAGEL_DEFAULT_YAML = get_deploy_config_path("ci/bagel.yaml")
-
 PROMPT = "A futuristic city skyline at twilight, cyberpunk style, ultra-detailed, high resolution."
 NEGATIVE_PROMPT = "low quality, blurry, distorted, deformed, watermark"
 
 SINGLE_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"})
 PARALLEL_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"}, num_cards=2)
-TP_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"}, num_cards=3)
-
-
-def _make_tp_cases(model: str, tp_size: int):
-    """Build Bagel TP test cases with devices auto-derived from tp_size.
-    Devices can not be set through CLI args, so we set them in the YAML.
-    """
-    # Stage 0 uses GPU 0, so place DiT TP ranks on GPU 1..N to
-    # avoid AR/DiT memory contention on one device.
-    devices = ",".join(str(i + 1) for i in range(tp_size))
-    stage_overrides = json.dumps(
-        {
-            "0": {"tensor_parallel_size": 1},
-            "1": {"devices": devices},
-        }
-    )
-    return [
-        pytest.param(
-            OmniServerParams(
-                model=model,
-                stage_config_path=_BAGEL_DEFAULT_YAML,
-                server_args=[
-                    "--stage-overrides",
-                    stage_overrides,
-                    "--cache-backend",
-                    "cache_dit",
-                    "--tensor-parallel-size",
-                    str(tp_size),
-                ],
-            ),
-            id=f"parallel_tp_{tp_size}",
-            marks=TP_FEATURE_MARKS,
-        ),
-    ]
 
 
 def _get_diffusion_feature_cases(model: str):
     """Return L4 diffusion feature cases for Bagel.
-    TeaCache, Cache-DiT, CFG-Parallel, Tensor-Parallel,
+    TeaCache, Cache-DiT, CFG-Parallel,
     Ulysses-SP, Ring-Attention, Layerwise Offloading.
     """
 
@@ -113,10 +73,6 @@ def _get_diffusion_feature_cases(model: str):
             id="parallel_cfg_2",
             marks=PARALLEL_FEATURE_MARKS,
         ),
-        # Tensor-Parallel size 2 (2 GPUs, Cache-DiT backend)
-        # Stage 1 (DiT) needs visible GPUs matching TP size; the default YAML
-        # only exposes device "0", so we patch it here.
-        *_make_tp_cases(model, tp_size=2),
         # Ulysses-SP degree=2 (2 GPUs)
         pytest.param(
             OmniServerParams(
@@ -181,7 +137,6 @@ def test_bagel(
     - TeaCache
     - Cache-DiT
     - CFG-Parallel (size=2)
-    - Tensor-Parallel (size=2)
     - Ulysses-SP (degree=2)
     - Ring-Attention (degree=2)
     - Layerwise Offloading