Reorganize CI and test files (#9027)

test/srt/lora/test_multi_lora_backend.py

@@ -0,0 +1,90 @@
+# Copyright 2023-2024 SGLang Team
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+import multiprocessing as mp
+import os
+import unittest
+from typing import List
+
+from utils import (
+    ALL_OTHER_MULTI_LORA_MODELS,
+    BACKENDS,
+    CI_MULTI_LORA_MODELS,
+    TORCH_DTYPES,
+    LoRAModelCase,
+    run_lora_test_one_by_one,
+)
+
+from sglang.test.test_utils import CustomTestCase, is_in_ci
+
+# All prompts are used at once in a batch.
+PROMPTS = [
+    "AI is a field of computer science focused on",
+    """
+    ### Instruction:
+    Tell me about llamas and alpacas
+    ### Response:
+    Llamas are large, long-necked animals with a woolly coat. They have two toes on each foot instead of three like other camelids.
+    ### Question:
+    What do you know about llamas?
+    ### Answer:
+    """,
+]
+
+
+class TestMultiLoRABackend(CustomTestCase):
+
+    def _run_multi_lora_test_on_model_cases(self, model_cases: List[LoRAModelCase]):
+        for model_case in model_cases:
+            # If skip_long_prompt is True, filter out prompts longer than 1000 characters.
+            batch_prompts = (
+                PROMPTS
+                if not model_case.skip_long_prompt
+                else [p for p in PROMPTS if len(p) < 1000]
+            )
+            for torch_dtype in TORCH_DTYPES:
+                for backend in BACKENDS:
+                    run_lora_test_one_by_one(
+                        batch_prompts,
+                        model_case,
+                        torch_dtype,
+                        max_new_tokens=32,
+                        backend=backend,
+                        test_tag="multi-lora-backend",
+                    )
+
+    def test_ci_lora_models(self):
+        self._run_multi_lora_test_on_model_cases(CI_MULTI_LORA_MODELS)
+
+    def test_all_lora_models(self):
+        if is_in_ci():
+            return
+
+        # Retain ONLY_RUN check here
+        filtered_models = []
+        for model_case in ALL_OTHER_MULTI_LORA_MODELS:
+            if "ONLY_RUN" in os.environ and os.environ["ONLY_RUN"] != model_case.base:
+                continue
+            filtered_models.append(model_case)
+
+        self._run_multi_lora_test_on_model_cases(filtered_models)
+
+
+if __name__ == "__main__":
+    try:
+        mp.set_start_method("spawn")
+    except RuntimeError:
+        pass
+
+    unittest.main(warnings="ignore")