Show correct error message on using BT for SDPA models (#1599)

show correct error message bt

optimum/bettertransformer/transformation.py

@@ -206,6 +206,12 @@ def transform(
             The converted model if the conversion has been successful.
         """
 
+        hf_config = model.config
+        if hf_config.model_type in ["falcon", "gpt_bigcode", "llama", "whisper"]:
+            raise ValueError(
+                f"Transformers now supports natively BetterTransformer optimizations (torch.nn.functional.scaled_dot_product_attention) for the model type {hf_config.model_type}. Please upgrade to transformers>=4.36 and torch>=2.1.1 to use it. Details: https://huggingface.co/docs/transformers/perf_infer_gpu_one#flashattention-and-memory-efficient-attention-through-pytorchs-scaleddotproductattention"
+            )
+
         # Check if we have to load the model using `accelerate`
         if hasattr(model, "hf_device_map"):
             load_accelerate = True
@@ -236,13 +242,6 @@ def transform(
                 f"BetterTransformer requires torch>=2.0 but {torch.__version__} is installed. Please upgrade PyTorch."
             )
 
-        hf_config = model.config
-
-        if hf_config.model_type in ["falcon", "gpt_bigcode", "llama", "whisper"]:
-            raise ValueError(
-                f"Transformers now supports natively BetterTransformer optimizations (torch.nn.functional.scaled_dot_product_attention) for the model type {hf_config.model_type}. Please upgrade to transformers>=4.36 and torch>=2.1.1 to use it. Details: https://huggingface.co/docs/transformers/perf_infer_gpu_one#flashattention-and-memory-efficient-attention-through-pytorchs-scaleddotproductattention"
-            )
-
         if load_accelerate:
             # Remove the hooks from the original model to avoid weights being on `meta` device.
             remove_hook_from_module(model, recurse=True)

tests/bettertransformer/test_audio.py

@@ -33,6 +33,16 @@
 ]
 
 
+class TestsWhisper(unittest.TestCase):
+    def test_error_message(self):
+        model = AutoModel.from_pretrained("openai/whisper-tiny")
+
+        with self.assertRaises(ValueError) as cm:
+            model = BetterTransformer.transform(model)
+
+        self.assertTrue("Transformers now supports natively BetterTransformer optimizations" in str(cm.exception))
+
+
 class BetterTransformersBarkTest(BetterTransformersTestMixin, unittest.TestCase):
     r"""
     Testing suite for Bark - tests all the tests defined in `BetterTransformersTestMixin`