Add support for Magcache

src/diffusers/__init__.py

@@ -163,16 +163,19 @@
     )
     _import_structure["hooks"].extend(
         [
+            "FLUX_MAG_RATIOS",
             "FasterCacheConfig",
             "FirstBlockCacheConfig",
             "HookRegistry",
             "LayerSkipConfig",
+            "MagCacheConfig",
             "PyramidAttentionBroadcastConfig",
             "SmoothedEnergyGuidanceConfig",
             "TaylorSeerCacheConfig",
             "apply_faster_cache",
             "apply_first_block_cache",
             "apply_layer_skip",
+            "apply_mag_cache",
             "apply_pyramid_attention_broadcast",
             "apply_taylorseer_cache",
         ]
@@ -895,16 +898,19 @@
             TangentialClassifierFreeGuidance,
         )
         from .hooks import (
+            FLUX_MAG_RATIOS,
             FasterCacheConfig,
             FirstBlockCacheConfig,
             HookRegistry,
             LayerSkipConfig,
+            MagCacheConfig,
             PyramidAttentionBroadcastConfig,
             SmoothedEnergyGuidanceConfig,
             TaylorSeerCacheConfig,
             apply_faster_cache,
             apply_first_block_cache,
             apply_layer_skip,
+            apply_mag_cache,
             apply_pyramid_attention_broadcast,
             apply_taylorseer_cache,
         )

src/diffusers/hooks/__init__.py

@@ -23,6 +23,7 @@
     from .hooks import HookRegistry, ModelHook
     from .layer_skip import LayerSkipConfig, apply_layer_skip
     from .layerwise_casting import apply_layerwise_casting, apply_layerwise_casting_hook
+    from .mag_cache import FLUX_MAG_RATIOS, MagCacheConfig, apply_mag_cache
     from .pyramid_attention_broadcast import PyramidAttentionBroadcastConfig, apply_pyramid_attention_broadcast
     from .smoothed_energy_guidance_utils import SmoothedEnergyGuidanceConfig
     from .taylorseer_cache import TaylorSeerCacheConfig, apply_taylorseer_cache

src/diffusers/hooks/_common.py

@@ -23,7 +23,13 @@
 _ATTENTION_CLASSES = (Attention, MochiAttention, AttentionModuleMixin)
 _FEEDFORWARD_CLASSES = (FeedForward, LuminaFeedForward)
 
-_SPATIAL_TRANSFORMER_BLOCK_IDENTIFIERS = ("blocks", "transformer_blocks", "single_transformer_blocks", "layers")
+_SPATIAL_TRANSFORMER_BLOCK_IDENTIFIERS = (
+    "blocks",
+    "transformer_blocks",
+    "single_transformer_blocks",
+    "layers",
+    "visual_transformer_blocks",
+)
 _TEMPORAL_TRANSFORMER_BLOCK_IDENTIFIERS = ("temporal_transformer_blocks",)
 _CROSS_TRANSFORMER_BLOCK_IDENTIFIERS = ("blocks", "transformer_blocks", "layers")
 

src/diffusers/hooks/_helpers.py

@@ -169,7 +169,7 @@ def _register_attention_processors_metadata():
 
 
 def _register_transformer_blocks_metadata():
-    from ..models.attention import BasicTransformerBlock
+    from ..models.attention import BasicTransformerBlock, JointTransformerBlock
     from ..models.transformers.cogvideox_transformer_3d import CogVideoXBlock
     from ..models.transformers.transformer_bria import BriaTransformerBlock
     from ..models.transformers.transformer_cogview4 import CogView4TransformerBlock
@@ -184,6 +184,7 @@ def _register_transformer_blocks_metadata():
         HunyuanImageSingleTransformerBlock,
         HunyuanImageTransformerBlock,
     )
+    from ..models.transformers.transformer_kandinsky import Kandinsky5TransformerDecoderBlock
     from ..models.transformers.transformer_ltx import LTXVideoTransformerBlock
     from ..models.transformers.transformer_mochi import MochiTransformerBlock
     from ..models.transformers.transformer_qwenimage import QwenImageTransformerBlock
@@ -331,6 +332,23 @@ def _register_transformer_blocks_metadata():
         ),
     )
 
+    TransformerBlockRegistry.register(
+        model_class=JointTransformerBlock,
+        metadata=TransformerBlockMetadata(
+            return_hidden_states_index=1,
+            return_encoder_hidden_states_index=0,
+        ),
+    )
+
+    # Kandinsky 5.0 (Kandinsky5TransformerDecoderBlock)
+    TransformerBlockRegistry.register(
+        model_class=Kandinsky5TransformerDecoderBlock,
+        metadata=TransformerBlockMetadata(
+            return_hidden_states_index=0,
+            return_encoder_hidden_states_index=None,
+        ),
+    )
+
 
 # fmt: off
 def _skip_attention___ret___hidden_states(self, *args, **kwargs):