[Feature] Stronger transformers modeling backend with TP, PP, MoE, VLMs, and torch compile (#19163)

test/registered/models/test_transformers_backend_eval.py

@@ -0,0 +1,43 @@
+"""A small end-to-end eval coverage for the transformers modeling backend."""
+
+import unittest
+from types import SimpleNamespace
+
+from sglang.test.ci.ci_register import register_cuda_ci
+from sglang.test.few_shot_gsm8k import run_eval
+from sglang.test.server_fixtures.default_fixture import DefaultServerBase
+
+register_cuda_ci(est_time=180, suite="stage-b-test-small-1-gpu")
+
+
+class TestTransformersBackendEval(DefaultServerBase):
+    model = "HuggingFaceTB/SmolLM3-3B"
+    gsm8k_num_questions = 30
+    gsm8k_accuracy_thres = 0.5
+    gsm8k_parallel = 30
+    other_args = [
+        "--model-impl",
+        "transformers",
+        "--enable-torch-compile",
+        "--torch-compile-max-bs",
+        "4",
+        "--disable-cuda-graph",
+    ]
+
+    def test_gsm8k(self):
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=self.gsm8k_num_questions,
+            max_new_tokens=512,
+            parallel=self.gsm8k_parallel,
+            host="127.0.0.1",
+            port=int(self.base_url.split(":")[-1]),
+        )
+        metrics = run_eval(args)
+        print(f"{metrics=}")
+        self.assertGreaterEqual(metrics["accuracy"], self.gsm8k_accuracy_thres)
+
+
+if __name__ == "__main__":
+    unittest.main()