fix import

Author: chenyushuo

pyproject.toml

@@ -76,6 +76,9 @@ megatron = [
     "transformer_engine[pytorch]==2.8.0",
     "mbridge>=0.13.0",
 ]
+tinker = [
+    "tinker",  # tinker requires python>=3.11
+]
 
 doc = [
     "sphinx",

trinity/common/config.py

@@ -1197,7 +1197,7 @@ def _check_tinker(self) -> None:
             item.model_name for item in service_client.get_server_capabilities().supported_models
         }
         if model.tinker.base_model not in supported_models:
-            print(supported_models)
+            logger.error(f"Supported models: {supported_models}")
             raise ValueError(f"{model.tinker.base_model} is not supported by tinker!")
         if model.tinker.base_model != model.model_path:
             logger.warning(

trinity/common/models/__init__.py

@@ -45,17 +45,18 @@ def create_inference_models(
     from ray.util.placement_group import placement_group, placement_group_table
     from ray.util.scheduling_strategies import PlacementGroupSchedulingStrategy
 
-    from trinity.common.models.tinker_model import TinkerModel
-    from trinity.common.models.vllm_model import vLLMRolloutModel
-
     logger = get_logger(__name__)
     engine_num = config.explorer.rollout_model.engine_num
     tensor_parallel_size = config.explorer.rollout_model.tensor_parallel_size
 
     rollout_engines = []
     if config.explorer.rollout_model.engine_type.startswith("vllm"):
+        from trinity.common.models.vllm_model import vLLMRolloutModel
+
         engine_cls = vLLMRolloutModel
     elif config.explorer.rollout_model.engine_type == "tinker":
+        from trinity.common.models.tinker_model import TinkerModel
+
         engine_cls = TinkerModel
         namespace = ray.get_runtime_context().namespace
         rollout_engines = [
@@ -152,7 +153,7 @@ def create_inference_models(
             model_config.engine_type = "vllm"
             model_config.bundle_indices = ",".join([str(bid) for bid in bundles_for_engine])
             engines.append(
-                ray.remote(vLLMRolloutModel)
+                ray.remote(engine_cls)
                 .options(
                     name=f"{config.explorer.name}_auxiliary_model_{i}_{j}",
                     num_cpus=0,