compute attn capability flags in normalizer instead of properties

src/axolotl/utils/schemas/config.py

@@ -1335,39 +1335,29 @@ class AxolotlInputConfig(
             return [ds_config.model_dump(exclude_none=True) for ds_config in ds_configs]
         return None
 
-    # --- Attention capability properties ---
+    # --- Attention capability flags (computed by normalize_attn_implementation) ---
 
-    @property
-    def attn_supports_packing(self) -> bool:
-        """True if attention supports varlen sample packing via position_ids.
-
-        Known varlen backends: flash, flex, xformers, sage.
-        Unknown strings (e.g., hub kernels like 'kernels-community/flash-attn3')
-        default to True since they generally support varlen.
-        """
-        if not self.attn_implementation:
-            return False
-        return self.attn_implementation not in _NON_PACKING_ATTN_IMPLS
-
-    @property
-    def attn_uses_flash_lib(self) -> bool:
-        """True if the backend uses axolotl's flash_attn monkeypatches.
-
-        Only for axolotl-managed FA setup (flash, s2). Hub kernels are
-        HF-managed and don't need these patches.
-        """
-        return self.attn_implementation in FLASH_ATTN_LIB_IMPLS
-
-    @property
-    def attn_needs_dtype_cast(self) -> bool:
-        """True if attention needs embedding dtype cast to fp16/bf16.
-
-        Unknown backends (hub kernels) default to True (safe -- harmless
-        if unnecessary, but missing cast causes errors).
-        """
-        if not self.attn_implementation:
-            return False
-        return self.attn_implementation not in _NO_DTYPE_CAST_ATTN_IMPLS
+    attn_supports_packing: bool | None = Field(
+        default=None,
+        json_schema_extra={
+            "description": "Whether the attention backend supports varlen sample packing. "
+            "Computed automatically from attn_implementation."
+        },
+    )
+    attn_uses_flash_lib: bool | None = Field(
+        default=None,
+        json_schema_extra={
+            "description": "Whether the attention backend requires axolotl's flash_attn "
+            "monkeypatches. Computed automatically from attn_implementation."
+        },
+    )
+    attn_needs_dtype_cast: bool | None = Field(
+        default=None,
+        json_schema_extra={
+            "description": "Whether the attention backend needs embedding dtype cast to "
+            "fp16/bf16. Computed automatically from attn_implementation."
+        },
+    )
 
     @model_validator(mode="before")
     @classmethod
@@ -1463,6 +1453,17 @@ class AxolotlInputConfig(
                     )
                     break
 
+        # Compute capability flags from the final attn_implementation value
+        impl = data.get("attn_implementation")
+        if impl:
+            data["attn_supports_packing"] = impl not in _NON_PACKING_ATTN_IMPLS
+            data["attn_uses_flash_lib"] = impl in FLASH_ATTN_LIB_IMPLS
+            data["attn_needs_dtype_cast"] = impl not in _NO_DTYPE_CAST_ATTN_IMPLS
+        else:
+            data["attn_supports_packing"] = False
+            data["attn_uses_flash_lib"] = False
+            data["attn_needs_dtype_cast"] = False
+
         return data
 
     @model_validator(mode="before")