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fix(awq): 修复低内存模式下apply_scale和apply_clip后所有子模块不在同一设备上的问题，添加_remove_accelerate_hooks函数来清理accelerate的hooks #184

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Merged
yghstill merged 1 commit into from
Jan 5, 2026
Merged

fix(awq): 修复低内存模式下apply_scale和apply_clip后所有子模块不在同一设备上的问题，添加_remove_accelerate_hooks函数来清理accelerate的hooks #184

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22 changes: 22 additions & 0 deletions angelslim/compressor/quant/modules/awq/awq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,20 @@
__all__ = ["AWQ"]


def _remove_accelerate_hooks(module):
for submodule in module.modules():
if hasattr(submodule, "_hf_hook"):
try:
from accelerate.hooks import remove_hook_from_module
remove_hook_from_module(submodule)
except ImportError:
# Should not happen if _hf_hook is present
delattr(submodule, "_hf_hook")
if hasattr(submodule, "_old_forward"):
submodule.forward = submodule._old_forward
delattr(submodule, "_old_forward")


class AWQ:
def __init__(
self,
Expand Down Expand Up @@ -156,6 +170,7 @@ def run(self, dataloader):
f"GPU Memory: {torch.cuda.memory_allocated() / 1024 ** 2:.2f} MB"
)

_remove_accelerate_hooks(layers[i])
layer = layers[i].to(dev)
if not self.low_memory:
outs = outs.to(dev)
Expand Down Expand Up @@ -232,6 +247,10 @@ def deduplicate_tensors(tensor_list):
)

self.scale_function.apply_scale(layer, scales_list, input_feat)

# Fix: Ensure all submodules are on the same device after apply_scale
# In low_memory mode, apply_scale may move weights to different devices
layer = layer.to(dev)
for scales in scales_list:
name = "language_model.encoder.layers.{}.{}.scale".format(i, scales[0])
self.scales_dict[name] = scales[2]
Expand All @@ -240,6 +259,9 @@ def deduplicate_tensors(tensor_list):
clip_list = self.clip_function.auto_clip(layer, input_feat)
self.clip_function.apply_clip(layer, clip_list)

# Fix: Ensure all submodules are on the same device after apply_clip
layer = layer.to(dev)

for j in range(min(self.inps.shape[1], nsamples)):
with torch.no_grad():
outs[j, :, :] = layer(
Expand Down
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