[ROCm][CI] Fix entrypoints tests and Python-only installation test on ROCm (#28979)

Signed-off-by: Andreas Karatzas <akaratza@amd.com>

tests/entrypoints/pooling/score/test_correctness_mteb.py

@@ -15,11 +15,6 @@ from tests.models.language.pooling_mteb_test.mteb_utils import (
 from tests.utils import RemoteOpenAIServer
 from vllm.platforms import current_platform
 
-if current_platform.is_rocm():
-    pytest.skip(
-        "Encoder self-attention is not implemented on ROCm.", allow_module_level=True
-    )
-
 os.environ["VLLM_LOGGING_LEVEL"] = "WARNING"
 
 MODEL_NAME = "cross-encoder/ms-marco-MiniLM-L-6-v2"
@@ -30,6 +25,10 @@ st_main_score = 0.33457
 def server():
     args = ["--runner", "pooling", "--enforce-eager", "--disable-uvicorn-access-log"]
 
+    # ROCm: Use Flex Attention to support encoder-only self-attention.
+    if current_platform.is_rocm():
+        args.extend(["--attention-backend", "FLEX_ATTENTION"])
+
     with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
         yield remote_server
 

tests/entrypoints/pooling/score/test_offline.py

@@ -11,16 +11,17 @@ from vllm import LLM, PoolingParams
 from vllm.distributed import cleanup_dist_env_and_memory
 from vllm.platforms import current_platform
 
-if current_platform.is_rocm():
-    pytest.skip(
-        "Encoder self-attention is not implemented on ROCm.", allow_module_level=True
-    )
-
 MODEL_NAME = "tomaarsen/Qwen3-Reranker-0.6B-seq-cls"
 
 
 @pytest.fixture(scope="module")
 def llm():
+    # ROCm: Use FLEX_ATTENTION backend as it's the only attention backend
+    # that supports encoder-only models on ROCm.
+    attention_config = None
+    if current_platform.is_rocm():
+        attention_config = {"backend": "FLEX_ATTENTION"}
+
     # pytest caches the fixture so we use weakref.proxy to
     # enable garbage collection
     llm = LLM(
@@ -30,6 +31,7 @@ def llm():
         gpu_memory_utilization=0.75,
         enforce_eager=True,
         seed=0,
+        attention_config=attention_config,
     )
 
     yield weakref.proxy(llm)

tests/entrypoints/pooling/score/test_online_rerank.py

@@ -11,11 +11,6 @@ from vllm.entrypoints.pooling.pooling.protocol import PoolingResponse
 from vllm.entrypoints.pooling.score.protocol import RerankResponse
 from vllm.platforms import current_platform
 
-if current_platform.is_rocm():
-    pytest.skip(
-        "Encoder self-attention is not implemented on ROCm.", allow_module_level=True
-    )
-
 MODEL_NAME = "BAAI/bge-reranker-base"
 DTYPE = "bfloat16"
 
@@ -24,6 +19,10 @@ DTYPE = "bfloat16"
 def server():
     args = ["--enforce-eager", "--max-model-len", "100", "--dtype", DTYPE]
 
+    # ROCm: Use Flex Attention to support encoder-only self-attention.
+    if current_platform.is_rocm():
+        args.extend(["--attention-backend", "FLEX_ATTENTION"])
+
     with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
         yield remote_server
 

tests/entrypoints/pooling/score/test_online_score.py

@@ -12,11 +12,6 @@ from tests.utils import RemoteOpenAIServer
 from vllm.entrypoints.pooling.score.protocol import ScoreResponse
 from vllm.platforms import current_platform
 
-if current_platform.is_rocm():
-    pytest.skip(
-        "Encoder self-attention is not implemented on ROCm.", allow_module_level=True
-    )
-
 MODELS = [
     {"name": "BAAI/bge-reranker-v2-m3", "is_cross_encoder": True},
     {"name": "BAAI/bge-base-en-v1.5", "is_cross_encoder": False},
@@ -44,6 +39,10 @@ def model(request):
 def server(model: dict[str, Any]):
     args = ["--enforce-eager", "--max-model-len", "100", "--dtype", DTYPE]
 
+    # ROCm: Use Flex Attention to support encoder-only self-attention.
+    if current_platform.is_rocm():
+        args.extend(["--attention-backend", "FLEX_ATTENTION"])
+
     with RemoteOpenAIServer(model["name"], args) as remote_server:
         yield remote_server
 

tests/standalone_tests/pytorch_nightly_dependency.sh

@@ -4,6 +4,11 @@
 set -e
 set -x
 
+if command -v rocminfo >/dev/null 2>&1; then
+  echo "Skipping test for ROCm platform"
+  exit 0
+fi
+
 cd /vllm-workspace/
 
 rm -rf .venv
@@ -36,7 +41,7 @@ if diff before.txt after.txt; then
   echo "torch version not overridden."
 else
   echo "torch version overridden by nightly_torch_test.txt, \
-  if the dependency is not triggered by the pytroch nightly test,\
+  if the dependency is not triggered by the pytorch nightly test,\
   please add the dependency to the list 'white_list' in tools/pre_commit/generate_nightly_torch_test.py"
   exit 1
 fi

vllm/entrypoints/pooling/embed/conftest.py

+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Pytest configuration for vLLM pooling embed tests."""
+
+import warnings
+
+import torch
+
+from vllm.platforms import current_platform
+
+
+def pytest_collection_modifyitems(config, items):
+    """Configure ROCm-specific settings based on collected tests."""
+    if not current_platform.is_rocm():
+        return
+
+    # Disable Flash/MemEfficient SDP on ROCm to avoid HF Transformers
+    # accuracy issues: https://github.com/vllm-project/vllm/issues/30167
+    # TODO: Remove once ROCm SDP accuracy issues are resolved on HuggingFace
+    torch.backends.cuda.enable_flash_sdp(False)
+    torch.backends.cuda.enable_mem_efficient_sdp(False)
+    torch.backends.cuda.enable_math_sdp(True)
+    warnings.warn(
+        "ROCm: Disabled flash_sdp and mem_efficient_sdp, enabled math_sdp "
+        "to avoid HuggingFace Transformers accuracy issues",
+        UserWarning,
+        stacklevel=1,
+    )