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Zero
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# 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)
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