108 lines
4.1 KiB
Python
108 lines
4.1 KiB
Python
# Copyright 2025 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ..utils.logging import get_logger
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logger = get_logger(__name__) # pylint: disable=invalid-name
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class CacheMixin:
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r"""
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A class for enable/disabling caching techniques on diffusion models.
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Supported caching techniques:
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- [Pyramid Attention Broadcast](https://huggingface.co/papers/2408.12588)
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- [FasterCache](https://huggingface.co/papers/2410.19355)
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"""
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_cache_config = None
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@property
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def is_cache_enabled(self) -> bool:
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return self._cache_config is not None
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def enable_cache(self, config) -> None:
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r"""
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Enable caching techniques on the model.
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Args:
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config (`Union[PyramidAttentionBroadcastConfig]`):
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The configuration for applying the caching technique. Currently supported caching techniques are:
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- [`~hooks.PyramidAttentionBroadcastConfig`]
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Example:
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```python
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>>> import torch
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>>> from diffusers import CogVideoXPipeline, PyramidAttentionBroadcastConfig
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>>> pipe = CogVideoXPipeline.from_pretrained("THUDM/CogVideoX-5b", torch_dtype=torch.bfloat16)
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>>> pipe.to("cuda")
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>>> config = PyramidAttentionBroadcastConfig(
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... spatial_attention_block_skip_range=2,
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... spatial_attention_timestep_skip_range=(100, 800),
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... current_timestep_callback=lambda: pipe.current_timestep,
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... )
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>>> pipe.transformer.enable_cache(config)
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```
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"""
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from ..hooks import (
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FasterCacheConfig,
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PyramidAttentionBroadcastConfig,
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apply_faster_cache,
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apply_pyramid_attention_broadcast,
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)
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if self.is_cache_enabled:
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raise ValueError(
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f"Caching has already been enabled with {type(self._cache_config)}. To apply a new caching technique, please disable the existing one first."
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)
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if isinstance(config, PyramidAttentionBroadcastConfig):
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apply_pyramid_attention_broadcast(self, config)
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elif isinstance(config, FasterCacheConfig):
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apply_faster_cache(self, config)
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else:
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raise ValueError(f"Cache config {type(config)} is not supported.")
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self._cache_config = config
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def disable_cache(self) -> None:
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from ..hooks import FasterCacheConfig, HookRegistry, PyramidAttentionBroadcastConfig
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from ..hooks.faster_cache import _FASTER_CACHE_BLOCK_HOOK, _FASTER_CACHE_DENOISER_HOOK
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from ..hooks.pyramid_attention_broadcast import _PYRAMID_ATTENTION_BROADCAST_HOOK
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if self._cache_config is None:
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logger.warning("Caching techniques have not been enabled, so there's nothing to disable.")
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return
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if isinstance(self._cache_config, PyramidAttentionBroadcastConfig):
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registry = HookRegistry.check_if_exists_or_initialize(self)
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registry.remove_hook(_PYRAMID_ATTENTION_BROADCAST_HOOK, recurse=True)
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elif isinstance(self._cache_config, FasterCacheConfig):
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registry = HookRegistry.check_if_exists_or_initialize(self)
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registry.remove_hook(_FASTER_CACHE_DENOISER_HOOK, recurse=True)
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registry.remove_hook(_FASTER_CACHE_BLOCK_HOOK, recurse=True)
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else:
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raise ValueError(f"Cache config {type(self._cache_config)} is not supported.")
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self._cache_config = None
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def _reset_stateful_cache(self, recurse: bool = True) -> None:
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from ..hooks import HookRegistry
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HookRegistry.check_if_exists_or_initialize(self).reset_stateful_hooks(recurse=recurse)
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