Split test_mla.py into two files (#4216)

.github/workflows/pr-test-amd.yml

@@ -90,11 +90,11 @@ jobs:
       - name: MLA TEST
         timeout-minutes: 20
         run: |
-          docker exec -w /sglang-checkout/test/srt ci_sglang python3 test_mla.py TestMLA
+          docker exec -w /sglang-checkout/test/srt ci_sglang python3 test_mla.py
 
   finish:
     needs: [
-      accuracy-test-1-gpu-amd
+      accuracy-test-1-gpu-amd, mla-test-1-gpu-amd
     ]
     runs-on: ubuntu-latest
     steps:

test/srt/run_suite.py

@@ -24,6 +24,7 @@ suites = {
         "test_gguf.py",
         "test_input_embeddings.py",
         "test_mla.py",
+        "test_mla_deepseek_v3.py",
         "test_mla_flashinfer.py",
         "test_mla_fp8.py",
         "test_json_constrained.py",

test/srt/test_mla.py

@@ -1,11 +1,7 @@
 import unittest
 from types import SimpleNamespace
 
-import requests
-import torch
-
 from sglang.srt.utils import kill_process_tree
-from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.run_eval import run_eval
 from sglang.test.test_utils import (
     DEFAULT_MLA_MODEL_NAME_FOR_TEST,
@@ -56,101 +52,5 @@ class TestMLA(unittest.TestCase):
         self.assertGreater(metrics["score"], 0.8)
 
 
-class TestDeepseekV3(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        cls.model = "lmsys/sglang-ci-dsv3-test"
-        cls.base_url = DEFAULT_URL_FOR_TEST
-        other_args = ["--trust-remote-code"]
-        if torch.cuda.is_available() and torch.version.cuda:
-            other_args.extend(["--enable-torch-compile", "--cuda-graph-max-bs", "2"])
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=other_args,
-        )
-
-    @classmethod
-    def tearDownClass(cls):
-        kill_process_tree(cls.process.pid)
-
-    def test_gsm8k(self):
-        args = SimpleNamespace(
-            num_shots=5,
-            data_path=None,
-            num_questions=200,
-            max_new_tokens=512,
-            parallel=128,
-            host="http://127.0.0.1",
-            port=int(self.base_url.split(":")[-1]),
-        )
-        metrics = run_eval_few_shot_gsm8k(args)
-        print(metrics)
-
-        self.assertGreater(metrics["accuracy"], 0.62)
-
-
-class TestDeepseekV3MTP(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        cls.model = "lmsys/sglang-ci-dsv3-test"
-        cls.base_url = DEFAULT_URL_FOR_TEST
-        other_args = ["--trust-remote-code"]
-        if torch.cuda.is_available() and torch.version.cuda:
-            other_args.extend(
-                [
-                    "--cuda-graph-max-bs",
-                    "2",
-                    "--disable-radix",
-                    "--enable-torch-compile",
-                    "--torch-compile-max-bs",
-                    "1",
-                    "--speculative-algorithm",
-                    "EAGLE",
-                    "--speculative-draft",
-                    "lmsys/sglang-ci-dsv3-test-NextN",
-                    "--speculative-num-steps",
-                    "2",
-                    "--speculative-eagle-topk",
-                    "4",
-                    "--speculative-num-draft-tokens",
-                    "4",
-                ]
-            )
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            other_args=other_args,
-        )
-
-    @classmethod
-    def tearDownClass(cls):
-        kill_process_tree(cls.process.pid)
-
-    def test_gsm8k(self):
-        requests.get(self.base_url + "/flush_cache")
-
-        args = SimpleNamespace(
-            num_shots=5,
-            data_path=None,
-            num_questions=200,
-            max_new_tokens=512,
-            parallel=128,
-            host="http://127.0.0.1",
-            port=int(self.base_url.split(":")[-1]),
-        )
-        metrics = run_eval_few_shot_gsm8k(args)
-        print(metrics)
-
-        self.assertGreater(metrics["accuracy"], 0.60)
-
-        server_info = requests.get(self.base_url + "/get_server_info")
-        avg_spec_accept_length = server_info.json()["avg_spec_accept_length"]
-        print(f"{avg_spec_accept_length=}")
-        self.assertGreater(avg_spec_accept_length, 2.5)
-
-
 if __name__ == "__main__":
     unittest.main()

test/srt/test_mla_deepseek_v3.py

@@ -0,0 +1,113 @@
+import unittest
+from types import SimpleNamespace
+
+import requests
+import torch
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    popen_launch_server,
+)
+
+
+class TestDeepseekV3(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = "lmsys/sglang-ci-dsv3-test"
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        other_args = ["--trust-remote-code"]
+        if torch.cuda.is_available() and torch.version.cuda:
+            other_args.extend(["--enable-torch-compile", "--cuda-graph-max-bs", "2"])
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=other_args,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=200,
+            max_new_tokens=512,
+            parallel=128,
+            host="http://127.0.0.1",
+            port=int(self.base_url.split(":")[-1]),
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(metrics)
+
+        self.assertGreater(metrics["accuracy"], 0.62)
+
+
+class TestDeepseekV3MTP(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = "lmsys/sglang-ci-dsv3-test"
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        other_args = ["--trust-remote-code"]
+        if torch.cuda.is_available() and torch.version.cuda:
+            other_args.extend(
+                [
+                    "--cuda-graph-max-bs",
+                    "2",
+                    "--disable-radix",
+                    "--enable-torch-compile",
+                    "--torch-compile-max-bs",
+                    "1",
+                    "--speculative-algorithm",
+                    "EAGLE",
+                    "--speculative-draft",
+                    "lmsys/sglang-ci-dsv3-test-NextN",
+                    "--speculative-num-steps",
+                    "2",
+                    "--speculative-eagle-topk",
+                    "4",
+                    "--speculative-num-draft-tokens",
+                    "4",
+                ]
+            )
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=other_args,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        requests.get(self.base_url + "/flush_cache")
+
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=200,
+            max_new_tokens=512,
+            parallel=128,
+            host="http://127.0.0.1",
+            port=int(self.base_url.split(":")[-1]),
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(metrics)
+
+        self.assertGreater(metrics["accuracy"], 0.60)
+
+        server_info = requests.get(self.base_url + "/get_server_info")
+        avg_spec_accept_length = server_info.json()["avg_spec_accept_length"]
+        print(f"{avg_spec_accept_length=}")
+        self.assertGreater(avg_spec_accept_length, 2.5)
+
+
+if __name__ == "__main__":
+    unittest.main()