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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)