[ROCm][CI] Fix flaky embedding chat test by using tolerance-based comparison (#35050)

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

tests/entrypoints/pooling/embed/test_online.py

@@ -58,13 +58,19 @@ if current_platform.is_rocm():
     torch.backends.cuda.enable_mem_efficient_sdp(False)
     torch.backends.cuda.enable_math_sdp(True)
 
+# On ROCm, floating-point reductions in attention and GEMM kernels are
+# non-associative and sensitive to batch geometry. Force LLM instances
+# into an identical, deterministic execution mode:
+ROCM_DETERMINISM_ARGS: list[str] = (
+    ["--max-num-seqs", "1"] if current_platform.is_rocm() else []
+)
+
 
 @pytest.fixture(scope="module")
 def server():
     args = [
         "--runner",
         "pooling",
-        # use half precision for speed and memory savings in CI environment
         "--dtype",
         DTYPE,
         "--enforce-eager",
@@ -72,12 +78,9 @@ def server():
         "512",
         "--chat-template",
         DUMMY_CHAT_TEMPLATE,
+        *ROCM_DETERMINISM_ARGS,
     ]
 
-    # 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
 
@@ -343,8 +346,15 @@ async def test_chat_request(
     assert chat_embeddings.id is not None
     assert completion_embeddings.id is not None
     assert chat_embeddings.created <= completion_embeddings.created
-    assert chat_embeddings.model_dump(exclude={"id", "created"}) == (
-        completion_embeddings.model_dump(exclude={"id", "created"})
+    # Use tolerance-based comparison for embeddings
+    check_embeddings_close(
+        embeddings_0_lst=[d.embedding for d in chat_embeddings.data],
+        embeddings_1_lst=[d.embedding for d in completion_embeddings.data],
+        name_0="chat",
+        name_1="completion",
+    )
+    assert chat_embeddings.model_dump(exclude={"id", "created", "data"}) == (
+        completion_embeddings.model_dump(exclude={"id", "created", "data"})
     )
 
     # test add_generation_prompt