chore: vendor sglang v0.5.10 snapshot

third_party/sglang/test/manual/test_whisper_cuda_graph.py

@@ -0,0 +1,161 @@
+"""
+Test Whisper model with CUDA graph support.
+
+This test verifies that:
+1. Whisper model works correctly with CUDA graph enabled (default)
+2. Cross-attention KV cache is properly managed through RadixAttention
+3. Output is consistent between CUDA graph and non-CUDA-graph modes
+
+Usage:
+    python test_whisper_cuda_graph.py
+
+Requires:
+    - A GPU with sufficient memory
+    - openai-whisper model (e.g., openai/whisper-large-v3)
+    - An audio file or URL for testing
+"""
+
+import io
+import unittest
+
+import requests
+
+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,
+)
+
+WHISPER_MODEL = "openai/whisper-large-v3"
+TEST_AUDIO_URL = "https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/1.flac"
+TEST_AUDIO_LOCAL = "/tmp/test_whisper_audio.flac"
+
+
+def get_audio_bytes():
+    """Get audio bytes, downloading if necessary."""
+    import os
+
+    if os.path.exists(TEST_AUDIO_LOCAL):
+        with open(TEST_AUDIO_LOCAL, "rb") as f:
+            return f.read()
+    resp = requests.get(TEST_AUDIO_URL, timeout=30)
+    resp.raise_for_status()
+    with open(TEST_AUDIO_LOCAL, "wb") as f:
+        f.write(resp.content)
+    return resp.content
+
+
+class TestWhisperCudaGraph(CustomTestCase):
+    """Test Whisper with CUDA graph enabled (default behavior)."""
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = WHISPER_MODEL
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                "--served-model-name",
+                "whisper",
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def _transcribe(self, language="en"):
+        """Send a transcription request via OpenAI-compatible audio endpoint."""
+        audio_bytes = get_audio_bytes()
+        response = requests.post(
+            self.base_url + "/v1/audio/transcriptions",
+            files={"file": ("audio.ogg", io.BytesIO(audio_bytes), "audio/ogg")},
+            data={
+                "model": "whisper",
+                "language": language,
+            },
+        )
+        self.assertEqual(response.status_code, 200, response.text)
+        return response.json()
+
+    def test_basic_transcription(self):
+        """Test that basic transcription works with CUDA graph."""
+        result = self._transcribe()
+        self.assertIn("text", result)
+        text = result["text"]
+        self.assertTrue(len(text) > 0, "Transcription should not be empty")
+        print(f"Transcription: {text}")
+
+    def test_multiple_sequential_requests(self):
+        """Test multiple sequential requests to verify CUDA graph replay consistency."""
+        results = []
+        for i in range(3):
+            result = self._transcribe()
+            self.assertIn("text", result)
+            results.append(result["text"])
+            print(f"Request {i+1}: {result['text'][:80]}...")
+
+        # All transcriptions of the same audio should be identical
+        for i in range(1, len(results)):
+            self.assertEqual(
+                results[0],
+                results[i],
+                f"Transcription {i+1} differs from first transcription",
+            )
+
+    def test_transcription_quality(self):
+        """Test that transcription quality is reasonable (contains expected words)."""
+        result = self._transcribe()
+        text = result["text"].lower()
+        # The test audio is a LibriSpeech sample about stew for dinner
+        self.assertIn("stew", text, f"Expected 'stew' in transcription: {text}")
+        self.assertIn("dinner", text, f"Expected 'dinner' in transcription: {text}")
+        print(f"Quality check passed: {result['text'][:80]}...")
+
+
+class TestWhisperNoCudaGraph(CustomTestCase):
+    """Test Whisper with CUDA graph explicitly disabled for comparison."""
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = WHISPER_MODEL
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                "--served-model-name",
+                "whisper",
+                "--disable-cuda-graph",
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_basic_transcription_no_cuda_graph(self):
+        """Test that transcription works without CUDA graph (baseline)."""
+        audio_bytes = get_audio_bytes()
+        response = requests.post(
+            self.base_url + "/v1/audio/transcriptions",
+            files={"file": ("audio.ogg", io.BytesIO(audio_bytes), "audio/ogg")},
+            data={
+                "model": "whisper",
+                "language": "en",
+            },
+        )
+        self.assertEqual(response.status_code, 200, response.text)
+        result = response.json()
+        self.assertIn("text", result)
+        self.assertTrue(len(result["text"]) > 0)
+        print(f"No CUDA graph transcription: {result['text'][:80]}...")
+
+
+if __name__ == "__main__":
+    unittest.main(verbosity=3)