init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

tests/e2e/pull_request/one_card/pooling/test_classification.py

@@ -0,0 +1,43 @@
+import huggingface_hub
+import torch
+from modelscope import snapshot_download  # type: ignore[import-untyped]
+from transformers import AutoModelForSequenceClassification
+
+from tests.e2e.conftest import (
+    HfRunner,
+    VllmRunner,
+    cleanup_dist_env_and_memory,
+    wait_until_npu_memory_free,
+)
+
+
+@wait_until_npu_memory_free(target_free_percentage=0.7)
+def test_qwen_pooling_classify_correctness() -> None:
+    model_name = snapshot_download(
+        "Howeee/Qwen2.5-1.5B-apeach",
+        local_files_only=huggingface_hub.constants.HF_HUB_OFFLINE,
+    )
+
+    prompts = [
+        "Hello, my name is",
+        "The president of the United States is",
+        "The capital of France is",
+        "The future of AI is what",
+    ]
+
+    with HfRunner(model_name, dtype="float32", auto_cls=AutoModelForSequenceClassification) as hf_runner:
+        hf_outputs = hf_runner.classify(prompts)
+    cleanup_dist_env_and_memory()
+
+    with VllmRunner(
+        model_name,
+        runner="pooling",
+        max_model_len=None,
+        cudagraph_capture_sizes=[4],
+    ) as vllm_runner:
+        vllm_outputs = vllm_runner.classify(prompts)
+
+    for hf_output, vllm_output in zip(hf_outputs, vllm_outputs):
+        hf_output = torch.tensor(hf_output)
+        vllm_output = torch.tensor(vllm_output)
+        assert torch.allclose(hf_output, vllm_output, 1e-2)