Spaces:
Paused
Paused
File size: 1,839 Bytes
135b069 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
# 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.
"""
Accelerate utilities: Utilities related to accelerate
"""
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def apply_forward_hook(method):
"""
Decorator that applies a registered CpuOffload hook to an arbitrary function rather than `forward`. This is useful
for cases where a PyTorch module provides functions other than `forward` that should trigger a move to the
appropriate acceleration device. This is the case for `encode` and `decode` in [`AutoencoderKL`].
This decorator looks inside the internal `_hf_hook` property to find a registered offload hook.
:param method: The method to decorate. This method should be a method of a PyTorch module.
"""
if not is_accelerate_available():
return method
accelerate_version = version.parse(accelerate.__version__).base_version
if version.parse(accelerate_version) < version.parse("0.17.0"):
return method
def wrapper(self, *args, **kwargs):
if hasattr(self, "_hf_hook") and hasattr(self._hf_hook, "pre_forward"):
self._hf_hook.pre_forward(self)
return method(self, *args, **kwargs)
return wrapper
|