[CI] Add per-job uv venv isolation and upgrade CI version to Cuda 13 (#23119)

Co-authored-by: Kangyan Zhou <zky314343421@gmail.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: Alison Shao <a.shao@wustl.edu>
Co-authored-by: Mick <mickjagger19@icloud.com>

test/registered/quant/test_awq.py

@@ -13,7 +13,7 @@ from sglang.test.test_utils import (
     popen_launch_server,
 )
 
-register_cuda_ci(est_time=209, suite="stage-b-test-1-gpu-large")
+register_cuda_ci(est_time=950, suite="stage-b-test-1-gpu-large")
 register_amd_ci(est_time=200, suite="stage-b-test-1-gpu-large-amd")
 
 

test/registered/quant/test_torchao.py

@@ -1,94 +0,0 @@
-import unittest
-
-import requests
-
-from sglang import Engine
-from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
-
-register_cuda_ci(est_time=124, suite="stage-b-test-1-gpu-small")
-register_amd_ci(est_time=230, suite="stage-b-test-1-gpu-small-amd")
-from sglang.lang.chat_template import get_chat_template_by_model_path
-from sglang.srt.utils import kill_process_tree
-from sglang.test.kits.eval_accuracy_kit import MMLUMixin
-from sglang.test.test_utils import (
-    DEFAULT_IMAGE_URL,
-    DEFAULT_MODEL_NAME_FOR_TEST,
-    DEFAULT_SMALL_VLM_MODEL_NAME_FOR_TEST,
-    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-    DEFAULT_URL_FOR_TEST,
-    CustomTestCase,
-    is_in_amd_ci,
-    popen_launch_server,
-)
-
-
-class TestTorchAO(CustomTestCase, MMLUMixin):
-    mmlu_score_threshold = 0.60
-    mmlu_num_examples = 64
-    mmlu_num_threads = 32
-
-    @classmethod
-    def setUpClass(cls):
-        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
-        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=["--torchao-config", "int4wo-128"],
-        )
-
-    @classmethod
-    def tearDownClass(cls):
-        kill_process_tree(cls.process.pid)
-
-    def run_decode(self, max_new_tokens):
-        response = requests.post(
-            self.base_url + "/generate",
-            json={
-                "text": "The capital of France is",
-                "sampling_params": {
-                    "temperature": 0,
-                    "max_new_tokens": max_new_tokens,
-                },
-                "ignore_eos": True,
-            },
-        )
-        return response.json()
-
-    def test_throughput(self):
-        import time
-
-        max_tokens = 256
-
-        tic = time.perf_counter()
-        res = self.run_decode(max_tokens)
-        tok = time.perf_counter()
-        print(res["text"])
-        throughput = max_tokens / (tok - tic)
-        print(f"Throughput: {throughput} tokens/s")
-        if is_in_amd_ci():
-            assert throughput >= 150
-        else:
-            assert throughput >= 210
-
-
-class TestTorchAOForVLM(CustomTestCase):
-    def test_vlm_generate(self):
-        model_path = DEFAULT_SMALL_VLM_MODEL_NAME_FOR_TEST
-        chat_template = get_chat_template_by_model_path(model_path)
-        text = f"{chat_template.image_token}What is in this picture? Answer: "
-
-        engine = Engine(
-            model_path=model_path,
-            max_total_tokens=512,
-            enable_multimodal=True,
-            torchao_config="fp8wo",
-        )
-        out = engine.generate([text], image_data=[DEFAULT_IMAGE_URL])
-        engine.shutdown()
-        self.assertGreater(len(out), 0)
-
-
-if __name__ == "__main__":
-    unittest.main()