[Kernels Attention] Change fallback logic to error out on explicit kernels request and include FA3

src/transformers/integrations/hub_kernels.py

@@ -152,7 +152,10 @@ def load_and_register_kernel(attn_implementation: str) -> None:
     if not is_kernel(attn_implementation):
         return
     if not _kernels_available:
-        raise ImportError("`kernels` is not installed. Please install it with `pip install kernels`.")
+        raise ImportError(
+            "`kernels` is either not installed or uses an incompatible version. "
+            "Please install the latest version with `pip install -U kernels`."
+        )
 
     # Need to be imported here as otherwise we have a circular import in `modeling_utils`
     from ..masking_utils import ALL_MASK_ATTENTION_FUNCTIONS

src/transformers/modeling_utils.py

@@ -2675,35 +2675,39 @@ def _check_and_adjust_attn_implementation(
             None to sdpa (to potentially eager).
         """
         applicable_attn_implementation = attn_implementation
+
         # If FA not installed, do not fail but use kernels instead
         if (
-            applicable_attn_implementation == "flash_attention_2"
+            attn_implementation is not None
+            and attn_implementation.startswith("flash_attention")
             and self._supports_flash_attn
-            and not is_flash_attn_2_available()
+            and not (is_flash_attn_2_available() or is_flash_attn_3_available())
             and is_kernels_available()
         ):
-            applicable_attn_implementation = "kernels-community/flash-attn"
+            if attn_implementation.endswith("2"):
+                applicable_attn_implementation = "kernels-community/flash-attn"
+            else:
+                applicable_attn_implementation = "kernels-community/vllm-flash-attn3"
+
         if is_kernel(applicable_attn_implementation):
             try:
                 load_and_register_kernel(applicable_attn_implementation)
                 # log that we used kernel fallback if successful
-                if attn_implementation == "flash_attention_2":
+                if attn_implementation.startswith("flash_attention"):
                     logger.warning_once(
-                        "You do not have `flash_attn` installed, using `kernels-community/flash-attn` from the `kernels` "
-                        "library instead!"
+                        f"You do not have `flash_attn` installed, using `{applicable_attn_implementation}` "
+                        "from the `kernels` library instead!"
                     )
             except Exception as e:
-                if attn_implementation == "flash_attention_2":
-                    self._flash_attn_2_can_dispatch()  # will fail as fa2 is not available but raise the proper exception
-                logger.warning_once(
-                    f"Could not find a kernel matching `{applicable_attn_implementation}` compatible with your device in the "
-                    f"hub:\n{e}.\nUsing default attention implementation instead (sdpa if available, eager otherwise)."
-                )
-                try:
-                    self._sdpa_can_dispatch(is_init_check)
-                    applicable_attn_implementation = "sdpa"
-                except (ValueError, ImportError):
-                    applicable_attn_implementation = "eager"
+                # raise the proper exception for requested flash attention
+                if attn_implementation.startswith("flash_attention"):
+                    if attn_implementation.endswith("2"):
+                        self._flash_attn_2_can_dispatch()
+                    else:
+                        self._flash_attn_3_can_dispatch()
+
+                # error properly out if a kernel was specifically requested
+                raise e
         else:
             applicable_attn_implementation = self.get_correct_attn_implementation(
                 applicable_attn_implementation, is_init_check

tests/utils/test_modeling_utils.py

@@ -88,6 +88,7 @@
 from transformers.utils.import_utils import (
     is_flash_attn_2_available,
     is_flash_attn_3_available,
+    is_kernels_available,
     is_torch_npu_available,
 )
 
@@ -2849,6 +2850,9 @@ def test_not_available_flash(self):
                 reason="FlashAttention2 is supported on Ascend NPU without using package `flash-attn`, ignore this test case."
             )
 
+        if is_kernels_available():
+            self.skipTest(reason="Please uninstall `kernels` package to run `test_not_available_flash`")
+
         with self.assertRaises(ImportError) as cm:
             _ = AutoModel.from_pretrained(
                 "hf-internal-testing/tiny-random-GPTBigCodeModel", attn_implementation="flash_attention_2"
@@ -2864,6 +2868,9 @@ def test_not_available_flash_with_config(self):
                 reason="FlashAttention2 is supported on Ascend NPU without using package `flash-attn`, ignore this test case."
             )
 
+        if is_kernels_available():
+            self.skipTest(reason="Please uninstall `kernels` package to run `test_not_available_flash_with_config`")
+
         config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeModel")
 
         with self.assertRaises(ImportError) as cm:
@@ -2875,6 +2882,41 @@ def test_not_available_flash_with_config(self):
 
         self.assertTrue("the package flash_attn seems to be not installed" in str(cm.exception))
 
+    def test_kernels_fallback(self):
+        if not is_kernels_available():
+            self.skipTest(reason="Please install `kernels` package to run `test_kernels_fallback`")
+
+        if is_flash_attn_2_available():
+            self.skipTest(reason="Please uninstall flash-attn package to run test_kernels_fallback")
+
+        if is_torch_npu_available():
+            self.skipTest(
+                reason="FlashAttention2 is supported on Ascend NPU without using package `flash-attn`, ignore this test case."
+            )
+
+        logger = logging.get_logger("transformers.modeling_utils")
+        with LoggingLevel(logging.WARNING):
+            with CaptureLogger(logger) as cl:
+                _ = AutoModel.from_pretrained(
+                    "hf-internal-testing/tiny-random-GPTBigCodeModel", attn_implementation="flash_attention_2"
+                )
+
+        self.assertTrue(
+            "You do not have `flash_attn` installed, using `kernels-community/flash-attn` from the `kernels` library instead!"
+            in cl.out
+        )
+
+    def test_not_available_kernels(self):
+        if is_kernels_available():
+            self.skipTest(reason="Please uninstall `kernels` package to run `test_not_available_kernels`")
+
+        with self.assertRaises(ImportError) as cm:
+            _ = AutoModel.from_pretrained(
+                "hf-tiny-model-private/tiny-random-MCTCTModel", attn_implementation="kernels-community/flash-attn"
+            )
+
+        self.assertTrue("`kernels` is either not installed or uses an incompatible version." in str(cm.exception))
+
 
 @require_torch
 class TestTensorSharing(TestCasePlus):