# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from ..utils.logging import get_logger logger = get_logger(__name__) # pylint: disable=invalid-name class CacheMixin: r""" A class for enable/disabling caching techniques on diffusion models. Supported caching techniques: - [Pyramid Attention Broadcast](https://huggingface.co/papers/2408.12588) - [FasterCache](https://huggingface.co/papers/2410.19355) """ _cache_config = None @property def is_cache_enabled(self) -> bool: return self._cache_config is not None def enable_cache(self, config) -> None: r""" Enable caching techniques on the model. Args: config (`Union[PyramidAttentionBroadcastConfig]`): The configuration for applying the caching technique. Currently supported caching techniques are: - [`~hooks.PyramidAttentionBroadcastConfig`] Example: ```python >>> import torch >>> from diffusers import CogVideoXPipeline, PyramidAttentionBroadcastConfig >>> pipe = CogVideoXPipeline.from_pretrained("THUDM/CogVideoX-5b", torch_dtype=torch.bfloat16) >>> pipe.to("cuda") >>> config = PyramidAttentionBroadcastConfig( ... spatial_attention_block_skip_range=2, ... spatial_attention_timestep_skip_range=(100, 800), ... current_timestep_callback=lambda: pipe.current_timestep, ... ) >>> pipe.transformer.enable_cache(config) ``` """ from ..hooks import ( FasterCacheConfig, PyramidAttentionBroadcastConfig, apply_faster_cache, apply_pyramid_attention_broadcast, ) if self.is_cache_enabled: raise ValueError( f"Caching has already been enabled with {type(self._cache_config)}. To apply a new caching technique, please disable the existing one first." ) if isinstance(config, PyramidAttentionBroadcastConfig): apply_pyramid_attention_broadcast(self, config) elif isinstance(config, FasterCacheConfig): apply_faster_cache(self, config) else: raise ValueError(f"Cache config {type(config)} is not supported.") self._cache_config = config def disable_cache(self) -> None: from ..hooks import FasterCacheConfig, HookRegistry, PyramidAttentionBroadcastConfig from ..hooks.faster_cache import _FASTER_CACHE_BLOCK_HOOK, _FASTER_CACHE_DENOISER_HOOK from ..hooks.pyramid_attention_broadcast import _PYRAMID_ATTENTION_BROADCAST_HOOK if self._cache_config is None: logger.warning("Caching techniques have not been enabled, so there's nothing to disable.") return if isinstance(self._cache_config, PyramidAttentionBroadcastConfig): registry = HookRegistry.check_if_exists_or_initialize(self) registry.remove_hook(_PYRAMID_ATTENTION_BROADCAST_HOOK, recurse=True) elif isinstance(self._cache_config, FasterCacheConfig): registry = HookRegistry.check_if_exists_or_initialize(self) registry.remove_hook(_FASTER_CACHE_DENOISER_HOOK, recurse=True) registry.remove_hook(_FASTER_CACHE_BLOCK_HOOK, recurse=True) else: raise ValueError(f"Cache config {type(self._cache_config)} is not supported.") self._cache_config = None def _reset_stateful_cache(self, recurse: bool = True) -> None: from ..hooks import HookRegistry HookRegistry.check_if_exists_or_initialize(self).reset_stateful_hooks(recurse=recurse)