fix VLLM->vLLM

Author: hjh0119

cookbook/client/twinkle/transformer/grpo.py

@@ -36,7 +36,7 @@
 from twinkle_client.dataloader import DataLoader
 from twinkle_client.dataset import Dataset
 from twinkle_client.model import MultiLoraTransformersModel
-from twinkle_client.sampler import VLLMSampler
+from twinkle_client.sampler import vLLMSampler
 
 logger = get_logger()
 
@@ -116,7 +116,7 @@ def train():
     model.set_template('Template', model_id=MODEL_ID)
 
     # Step 4: Configure the sampler
-    sampler = VLLMSampler(model_id=MODEL_ID)
+    sampler = vLLMSampler(model_id=MODEL_ID)
     sampler.set_template('Template', model_id=MODEL_ID)
 
     # Step 5: Setup metrics and advantage function

cookbook/client/twinkle/transformer/sampler.py

@@ -17,7 +17,7 @@
 
 from twinkle import get_logger
 from twinkle_client import init_twinkle_client
-from twinkle_client.sampler import VLLMSampler
+from twinkle_client.sampler import vLLMSampler
 
 logger = get_logger()
 
@@ -39,7 +39,7 @@ def sample():
     )
 
     # Step 3: Create the sampler client pointing to the model on the server
-    sampler = VLLMSampler(model_id=MODEL_ID)
+    sampler = vLLMSampler(model_id=MODEL_ID)
 
     # Step 4: Set the chat template so the sampler can encode Trajectory inputs
     sampler.set_template('Template', model_id=MODEL_ID)

src/twinkle/metric/loss.py

@@ -65,5 +65,5 @@ def calculate(self):
         if avg_loss is not None:
             results['loss'] = f'{avg_loss:.4f}'
         if grad_norm > 0:
-            results['grad_norm'] = f'{grad_norm:.2f}'
-        return results
+            results['grad_norm'] = f'{grad_norm:.6f}'
+        return results

src/twinkle/server/twinkle/sampler.py

@@ -163,9 +163,9 @@ def __init__(self, nproc_per_node: int, device_group: Dict[str, Any],
 
             # Initialize sampler based on type
             if sampler_type == 'vllm':
-                from twinkle.sampler import VLLMSampler
+                from twinkle.sampler import vLLMSampler
                 sampler_kwargs = engine_args or {}
-                self.sampler = VLLMSampler(
+                self.sampler = vLLMSampler(
                     model_id=model_id,
                     engine_args=sampler_kwargs,
                     device_mesh=self.device_mesh,

tests/sampler/test_sampler.py

@@ -239,7 +239,7 @@ def test_set_template(self):
 # =============================================================================
 
 @pytest.mark.skip(reason="Requires model and GPU")
-class TestVLLMSamplerIntegration:
+class TestvLLMSamplerIntegration:
     """Integration tests for vLLMSampler."""
 
     def test_sample_with_trajectory(self):