readme updates

example_trainer/trainers.py

@@ -217,6 +217,74 @@ def train_shared_vllm(config: TrainingConfig):
         else:
             print(f"  ✗ Modification didn't stick - tensor may be a copy!")
     
+    # === CRITICAL TEST: Does vLLM SEE weight modifications? ===
+    print(f"\n  [CRITICAL] Testing if vLLM sees weight modifications...")
+    try:
+        import requests
+        
+        test_prompt = "2+2="
+        vllm_url = f"http://localhost:{config.vllm_port}"
+        
+        # Get baseline output from vLLM
+        response1 = requests.post(
+            f"{vllm_url}/generate",
+            json={"prompt": test_prompt, "max_tokens": 3, "temperature": 0.0},
+            timeout=30,
+        )
+        baseline_output = response1.json().get("text", [""])[0] if response1.status_code == 200 else "ERROR"
+        
+        # CORRUPT a weight dramatically (this should break the model)
+        embed_param = None
+        for name, param in model.named_parameters():
+            if "embed_tokens" in name:
+                embed_param = param
+                break
+        
+        if embed_param is not None:
+            original_embed = embed_param.data[0, :10].clone()
+            
+            # Corrupt the embedding with extreme values
+            embed_param.data[0, :10] = 1000.0
+            
+            # Query vLLM again - if sharing works, output should be GARBAGE
+            response2 = requests.post(
+                f"{vllm_url}/generate",
+                json={"prompt": test_prompt, "max_tokens": 3, "temperature": 0.0},
+                timeout=30,
+            )
+            corrupted_output = response2.json().get("text", [""])[0] if response2.status_code == 200 else "ERROR"
+            
+            # Restore the embedding
+            embed_param.data[0, :10] = original_embed
+            
+            # Query vLLM again - should be back to normal
+            response3 = requests.post(
+                f"{vllm_url}/generate",
+                json={"prompt": test_prompt, "max_tokens": 3, "temperature": 0.0},
+                timeout=30,
+            )
+            restored_output = response3.json().get("text", [""])[0] if response3.status_code == 200 else "ERROR"
+            
+            print(f"    Baseline vLLM output:  '{baseline_output}'")
+            print(f"    Corrupted vLLM output: '{corrupted_output}'")
+            print(f"    Restored vLLM output:  '{restored_output}'")
+            
+            # Check if vLLM saw the corruption
+            if corrupted_output != baseline_output:
+                print(f"  ✓✓✓ vLLM SEES WEIGHT UPDATES! Output changed when weights corrupted.")
+                if restored_output == baseline_output:
+                    print(f"  ✓✓✓ Output restored after weight restoration. SHARING IS WORKING!")
+                else:
+                    print(f"  ⚠ Output didn't fully restore - may need vLLM cache clear")
+            else:
+                print(f"  ✗✗✗ vLLM DID NOT SEE CORRUPTION - SHARING IS BROKEN!")
+                print(f"      vLLM may have internal weight copies/cache.")
+                print(f"      The IPC attachment gives write access but vLLM doesn't read from it.")
+    except Exception as e:
+        import traceback
+        print(f"  Critical test failed: {e}")
+        traceback.print_exc()
+    
     # Now test vLLM logprobs vs trainer logprobs
     print(f"\n  Testing logprob alignment with vLLM...")
     try: