start kernelize.

src/diffusers/models/attention.py

@@ -20,6 +20,7 @@ import torch.nn.functional as F
 
 from ..utils import deprecate, logging
 from ..utils.import_utils import is_torch_npu_available, is_torch_xla_available, is_xformers_available
+from ..utils.kernels_utils import use_kernel_forward_from_hub
 from ..utils.torch_utils import maybe_allow_in_graph
 from .activations import GEGLU, GELU, ApproximateGELU, FP32SiLU, LinearActivation, SwiGLU
 from .attention_processor import Attention, AttentionProcessor, JointAttnProcessor2_0
@@ -1669,6 +1670,7 @@ class FreeNoiseTransformerBlock(nn.Module):
         return hidden_states
 
 
+@use_kernel_forward_from_hub("MLP")
 class FeedForward(nn.Module):
     r"""
     A feed-forward layer.

src/diffusers/models/normalization.py

@@ -21,6 +21,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 
 from ..utils import is_torch_npu_available, is_torch_version
+from ..utils.kernels_utils import use_kernel_forward_from_hub
 from .activations import get_activation
 from .embeddings import CombinedTimestepLabelEmbeddings, PixArtAlphaCombinedTimestepSizeEmbeddings
 
@@ -508,6 +509,7 @@ else:
             return F.layer_norm(input, self.dim, self.weight, self.bias, self.eps)
 
 
+@use_kernel_forward_from_hub("RMSNorm")
 class RMSNorm(nn.Module):
     r"""
     RMS Norm as introduced in https://huggingface.co/papers/1910.07467 by Zhang et al.

src/diffusers/utils/kernels_utils.py

@@ -1,3 +1,5 @@
+from typing import Union
+
 from ..utils import get_logger
 from .import_utils import is_kernels_available
 
@@ -21,3 +23,43 @@ def _get_fa3_from_hub():
         except Exception as e:
             logger.error(f"An error occurred while fetching kernel '{_DEFAULT_HUB_ID_FA3}' from the Hub: {e}")
             raise
+
+
+if is_kernels_available():
+    from kernels import (
+        Device,
+        LayerRepository,
+        register_kernel_mapping,
+        replace_kernel_forward_from_hub,
+        use_kernel_forward_from_hub,
+    )
+
+    _KERNEL_MAPPING: dict[str, dict[Union[Device, str], LayerRepository]] = {
+        "RMSNorm": {
+            "cuda": LayerRepository(repo_id="kernels-community/liger_kernels", layer_name="LigerRMSNorm"),
+        },
+        "MLP": {"cuda": LayerRepository(repo_id="medmekk/triton-llama-mlp", layer_name="TritonLlamaMLP")},
+    }
+
+    register_kernel_mapping(_KERNEL_MAPPING)
+
+else:
+    # Stub to make decorators int transformers work when `kernels`
+    # is not installed.
+    def use_kernel_forward_from_hub(*args, **kwargs):
+        def decorator(cls):
+            return cls
+
+        return decorator
+
+    class LayerRepository:
+        def __init__(self, *args, **kwargs):
+            raise RuntimeError("LayerRepository requires `kernels` to be installed. Run `pip install kernels`.")
+
+    def replace_kernel_forward_from_hub(*args, **kwargs):
+        raise RuntimeError(
+            "replace_kernel_forward_from_hub requires `kernels` to be installed. Run `pip install kernels`."
+        )
+
+    def register_kernel_mapping(*args, **kwargs):
+        raise RuntimeError("register_kernel_mapping requires `kernels` to be installed. Run `pip install kernels`.")