[CI] Split pooling from entrypoints Test (#24632)

Signed-off-by: wang.yuqi <noooop@126.com>

tests/entrypoints/pooling/llm/test_embedding.py

@@ -0,0 +1,55 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import weakref
+
+import pytest
+import torch
+import torch.nn.functional as F
+
+from vllm import LLM, PoolingParams
+from vllm.distributed import cleanup_dist_env_and_memory
+
+MODEL_NAME = "intfloat/multilingual-e5-small"
+
+prompts = ["The chef prepared a delicious meal."]
+
+
+@pytest.fixture(scope="module")
+def llm():
+    # pytest caches the fixture so we use weakref.proxy to
+    # enable garbage collection
+    llm = LLM(model=MODEL_NAME,
+              max_num_batched_tokens=32768,
+              tensor_parallel_size=1,
+              gpu_memory_utilization=0.75,
+              enforce_eager=True,
+              seed=0)
+
+    yield weakref.proxy(llm)
+
+    del llm
+
+    cleanup_dist_env_and_memory()
+
+
+@pytest.mark.skip_global_cleanup
+def test_pooling_params(llm: LLM):
+
+    def get_outputs(normalize):
+        outputs = llm.embed(prompts,
+                            pooling_params=PoolingParams(normalize=normalize),
+                            use_tqdm=False)
+        return torch.tensor([x.outputs.embedding for x in outputs])
+
+    default = get_outputs(normalize=None)
+    w_normal = get_outputs(normalize=True)
+    wo_normal = get_outputs(normalize=False)
+
+    assert torch.allclose(default, w_normal,
+                          atol=1e-2), "Default should use normal."
+    assert not torch.allclose(w_normal, wo_normal,
+                              atol=1e-2), "wo_normal should not use normal."
+    assert torch.allclose(
+        w_normal, F.normalize(wo_normal, p=2, dim=-1),
+        atol=1e-2), "w_normal should be close to normal(wo_normal)."