chore: vendor sglang v0.5.10 snapshot

2026-04-24 12:29:36 +00:00
parent 78f0d15221
commit bded08301f
4308 changed files with 1200894 additions and 2 deletions
--- a/third_party/sglang/test/srt/xpu/test_deepseek_ocr.py
+++ b/third_party/sglang/test/srt/xpu/test_deepseek_ocr.py
@@ -0,0 +1,123 @@
+"""
+python3 -m unittest test_deepseek_ocr.py
+"""
+
+import gc
+import json
+import os
+import unittest
+from pathlib import Path
+
+import requests
+from transformers import AutoTokenizer
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    popen_launch_server,
+)
+
+
+class TestDeepSeekOCR(CustomTestCase):
+    @classmethod
+    def _cleanup_xpu_memory(cls):
+        gc.collect()
+        try:
+            import torch
+
+            if hasattr(torch, "xpu") and torch.xpu.is_available():
+                torch.xpu.synchronize()
+                torch.xpu.empty_cache()
+        except Exception:
+            # Best-effort cleanup only; tests should continue if cleanup is unavailable.
+            pass
+
+    @classmethod
+    def setUpClass(cls):
+        cls._cleanup_xpu_memory()
+        cls.model = "deepseek-ai/DeepSeek-OCR"
+        cls.tokenizer = AutoTokenizer.from_pretrained(
+            cls.model, use_fast=False, trust_remote_code=True
+        )
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.image_path = str(
+            (Path(__file__).resolve().parents[3] / "examples/assets/example_image.png")
+        )
+        if not os.path.exists(cls.image_path):
+            raise FileNotFoundError(f"Image not found: {cls.image_path}")
+        cls.common_args = [
+            "--device",
+            "xpu",
+            "--attention-backend",
+            "intel_xpu",
+        ]
+        os.environ["SGLANG_USE_SGL_XPU"] = "1"
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                *cls.common_args,
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        """Fixture that is run once after all tests in the class."""
+        if hasattr(cls, "process") and cls.process:
+            kill_process_tree(cls.process.pid)
+        cls._cleanup_xpu_memory()
+
+    def get_request_json(self, max_new_tokens=32, n=1):
+        response = requests.post(
+            self.base_url + "/generate",
+            json={
+                "text": "<image>\n<|grounding|>Convert the document to pure text.",
+                "image_data": self.image_path,
+                "sampling_params": {
+                    "temperature": 0 if n == 1 else 0.5,
+                    "max_new_tokens": max_new_tokens,
+                },
+            },
+        )
+        return response.json()
+
+    def run_decode(
+        self,
+        max_new_tokens=128,
+        n=1,
+    ):
+
+        ret = self.get_request_json(max_new_tokens=max_new_tokens, n=n)
+        print(json.dumps(ret, indent=2))
+
+        def assert_one_item(item):
+            if item["meta_info"]["finish_reason"]["type"] == "stop":
+                self.assertEqual(
+                    item["meta_info"]["finish_reason"]["matched"],
+                    self.tokenizer.eos_token_id,
+                )
+            elif item["meta_info"]["finish_reason"]["type"] == "length":
+                self.assertEqual(
+                    len(item["output_ids"]), item["meta_info"]["completion_tokens"]
+                )
+                self.assertEqual(len(item["output_ids"]), max_new_tokens)
+
+        # Determine whether to assert a single item or multiple items based on n
+        if n == 1:
+            assert_one_item(ret)
+        else:
+            self.assertEqual(len(ret), n)
+            for i in range(n):
+                assert_one_item(ret[i])
+
+        print("=" * 100)
+
+    def test_moe(self):
+        self.run_decode()
+
+
+if __name__ == "__main__":
+    unittest.main()