Update inference.py

inference.py

@@ -302,7 +302,8 @@ class GenerativeInferenceModel:
         try:
             print(f"\n=== Running model integrity check for {model_type} ===")
             # Create a deterministic test input directly on the correct device
-            test_input = torch.zeros(1, 3, 224, 224, device=device)
+            H = W = MODEL_PREPROC.get(model_type, {"size": 224})["size"]
+            test_input = torch.zeros(1, 3, H, W, device=device)
             test_input[0, 0, 100:124, 100:124] = 0.5  # Red square
             
             # Run forward pass
@@ -705,6 +706,8 @@ class GenerativeInferenceModel:
             norm_mean=pre["mean"],
             norm_std=pre["std"]
         )
+
+        print(f"[PREPROC] {model_type}: size={pre['size']} mean={pre['mean']} std={pre['std']} (transform normalize=False; model has internal normalizer)")
         
         # Special handling for GradModulation as in original
         if config['loss_infer'] == 'GradModulation' and 'misc_info' in config and 'grad_modulation' in config['misc_info']: