[Transformer Optimization]Return model directly for unknown model type (

microsoft#18642)

This pull request is used to improves the handling of unsupported model
types in the optimization process.

onnxruntime/python/tools/transformers/optimizer.py

@@ -209,6 +209,10 @@ def optimize_by_fusion(
     if model_type not in ["bert", "swin", "unet", "vae", "clip"] and (num_heads == 0 or hidden_size == 0):
         logger.warning(f"Please specify parameters of num_heads and hidden_size for model_type {model_type}")
 
+    if model_type not in MODEL_TYPES:
+        logger.warning(f"Unsupported model type: {model_type} for graph fusion, directly return model.")
+        return OnnxModel(model)
+
     (optimizer_class, producer, _) = MODEL_TYPES[model_type]
 
     if model.producer_name and producer != model.producer_name:
@@ -290,6 +294,10 @@ def optimize_model(
     """
     assert opt_level is None or opt_level in [0, 1, 2, 99]
 
+    if model_type not in MODEL_TYPES:
+        logger.warning(f"Unsupported model type: {model_type} for optimization, directly return model.")
+        return OnnxModel(load_model(input))
+
     (optimizer_class, _producer, default_opt_level) = MODEL_TYPES[model_type]
 
     if opt_level is None: