Merge branch 'main' into update-kernel-hub-repos

Fix torchrun command argument order in docs

docs/source/en/training/distributed_inference.md

@@ -111,7 +111,7 @@ if __name__ == "__main__":
 Call `torchrun` to run the inference script and use the `--nproc_per_node` argument to set the number of GPUs to use.
 
 ```bash
-torchrun run_distributed.py --nproc_per_node=2
+torchrun --nproc_per_node=2 run_distributed.py
 ```
 
 ## device_map

src/diffusers/models/attention_dispatch.py

@@ -38,6 +38,7 @@ from ..utils import (
     is_flash_attn_available,
     is_flash_attn_version,
     is_kernels_available,
+    is_kernels_version,
     is_sageattention_available,
     is_sageattention_version,
     is_torch_npu_available,
@@ -318,6 +319,7 @@ class _HubKernelConfig:
     repo_id: str
     function_attr: str
     revision: str | None = None
+    version: int | None = None
     kernel_fn: Callable | None = None
     wrapped_forward_attr: str | None = None
     wrapped_backward_attr: str | None = None
@@ -327,27 +329,31 @@ class _HubKernelConfig:
 
 # Registry for hub-based attention kernels
 _HUB_KERNELS_REGISTRY: dict["AttentionBackendName", _HubKernelConfig] = {
-    # TODO: temporary revision for now. Remove when merged upstream into `main`.
     AttentionBackendName._FLASH_3_HUB: _HubKernelConfig(
-        repo_id="kernels-community/flash-attn3", function_attr="flash_attn_func", revision="fake-ops-return-probs"
+        repo_id="kernels-community/flash-attn3", function_attr="flash_attn_func", version=1
     ),
     AttentionBackendName._FLASH_3_VARLEN_HUB: _HubKernelConfig(
         repo_id="kernels-community/flash-attn3",
         function_attr="flash_attn_varlen_func",
-        # revision="fake-ops-return-probs",
+        version=1,
     ),
     AttentionBackendName.FLASH_HUB: _HubKernelConfig(
         repo_id="kernels-community/flash-attn2",
         function_attr="flash_attn_func",
+        version=1,
         revision=None,
         wrapped_forward_attr="flash_attn_interface._wrapped_flash_attn_forward",
         wrapped_backward_attr="flash_attn_interface._wrapped_flash_attn_backward",
     ),
     AttentionBackendName.FLASH_VARLEN_HUB: _HubKernelConfig(
-        repo_id="kernels-community/flash-attn2", function_attr="flash_attn_varlen_func", revision=None
+        repo_id="kernels-community/flash-attn2",
+        function_attr="flash_attn_varlen_func",
+        version=1,
     ),
     AttentionBackendName.SAGE_HUB: _HubKernelConfig(
-        repo_id="kernels-community/sage_attention", function_attr="sageattn", revision=None
+        repo_id="kernels-community/sage-attention",
+        function_attr="sageattn",
+        version=1,
     ),
 }
 
@@ -517,6 +523,10 @@ def _check_attention_backend_requirements(backend: AttentionBackendName) -> None
             raise RuntimeError(
                 f"Backend '{backend.value}' is not usable because the `kernels` package isn't available. Please install it with `pip install kernels`."
             )
+        if not is_kernels_version(">=", "0.12"):
+            raise RuntimeError(
+                f"Backend '{backend.value}' needs to be used with a `kernels` version of at least 0.12. Please update with `pip install -U kernels`."
+            )
 
     elif backend == AttentionBackendName.AITER:
         if not _CAN_USE_AITER_ATTN:

src/diffusers/utils/__init__.py

@@ -86,6 +86,7 @@ from .import_utils import (
     is_inflect_available,
     is_invisible_watermark_available,
     is_kernels_available,
+    is_kernels_version,
     is_kornia_available,
     is_librosa_available,
     is_matplotlib_available,

src/diffusers/utils/import_utils.py

@@ -724,6 +724,22 @@ def is_transformers_version(operation: str, version: str):
     return compare_versions(parse(_transformers_version), operation, version)
 
 
+@cache
+def is_kernels_version(operation: str, version: str):
+    """
+    Compares the current Kernels version to a given reference with an operation.
+
+    Args:
+        operation (`str`):
+            A string representation of an operator, such as `">"` or `"<="`
+        version (`str`):
+            A version string
+    """
+    if not _kernels_available:
+        return False
+    return compare_versions(parse(_kernels_version), operation, version)
+
+
 @cache
 def is_hf_hub_version(operation: str, version: str):
     """