Update inference.py

inference.py

@@ -694,12 +694,16 @@ class GenerativeInferenceModel:
         
         # Prepare image tensor - match original code's conditional transform
         load_start = time.time()
-        use_norm = config['inference_normalization'] == 'on'
+        # Pick the right preproc for this model
+        pre = self.model_preproc.get(model_type, {"size": 224, "mean": IMAGENET_MEAN, "std": IMAGENET_STD})
+        
+        # IMPORTANT: the model already includes a NormalizeByChannelMeanStd as layer 0,
+        # so do NOT normalize again here, or you’ll double-normalize.
         custom_transform = get_transform(
-            input_size=224, 
-            normalize=use_norm, 
-            norm_mean=IMAGENET_MEAN, 
-            norm_std=IMAGENET_STD
+            input_size=pre["size"],   # 112 for resnet50_robust_face
+            normalize=False,          # leave False; model handles normalization internally
+            norm_mean=pre["mean"],
+            norm_std=pre["std"]
         )
         
         # Special handling for GradModulation as in original