ostris/ai-toolkit
1
0
Fork 0
mirror of https://github.com/ostris/ai-toolkit.git synced 2026-01-26 16:39:47 +00:00
Code Issues Packages Projects Releases Wiki Activity

Offload ARA with the layer if doing layer offloading. Add support to offload the LoRA. Still needs optimizer support

Browse Source
This commit is contained in:
Jaret Burkett
2025-10-21 06:03:27 -06:00
parent 76ce757e0c
commit 0d8a33dc16
5 changed files with 37 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
toolkit/config_modules.py
View File

@@ -208,6 +208,9 @@ class NetworkConfig:
# for multi stage models
self.split_multistage_loras = kwargs.get('split_multistage_loras', True)
# ramtorch, doesn't work yet
self.layer_offloading = kwargs.get('layer_offloading', False)
AdapterTypes = Literal['t2i', 'ip', 'ip+', 'clip', 'ilora', 'photo_maker', 'control_net', 'control_lora', 'i2v']

17
toolkit/memory_management/manager.py
View File

@@ -108,6 +108,14 @@ class MemoryManager:
LinearLayerMemoryManager.attach(
child_module, module._memory_manager
)
# attach to ARA as well
if hasattr(child_module, "ara_lora_ref"):
ara = child_module.ara_lora_ref()
if ara not in modules_processed:
MemoryManager.attach(
ara,
device,
)
modules_processed.append(child_module)
elif (
child_module.__class__.__name__ in CONV_MODULES
@@ -125,6 +133,15 @@ class MemoryManager:
ConvLayerMemoryManager.attach(
child_module, module._memory_manager
)
# attach to ARA as well
if hasattr(child_module, "ara_lora_ref"):
ara = child_module.ara_lora_ref()
if ara not in modules_processed:
MemoryManager.attach(
ara,
device,
)
modules_processed.append(ara)
modules_processed.append(child_module)
elif child_module.__class__.__name__ in UNMANAGED_MODULES or any(
inc in child_module.__class__.__name__

4
toolkit/memory_management/manager_modules.py
View File

@@ -583,6 +583,8 @@ class LinearLayerMemoryManager(BaseLayerMemoryManager):
self.module.ara_lora_ref().org_forward = _mm_forward
else:
self.module.forward = _mm_forward
self.module._memory_management_device = self.manager.process_device
class ConvLayerMemoryManager(BaseLayerMemoryManager):
@@ -638,3 +640,5 @@ class ConvLayerMemoryManager(BaseLayerMemoryManager):
self.module.ara_lora_ref().org_forward = _mm_forward
else:
self.module.forward = _mm_forward
self.module._memory_management_device = self.manager.process_device

6
toolkit/network_mixins.py
View File

@@ -718,12 +718,18 @@ class ToolkitNetworkMixin:
if hasattr(first_module, 'lora_down'):
device = first_module.lora_down.weight.device
dtype = first_module.lora_down.weight.dtype
if hasattr(first_module.lora_down, '_memory_management_device'):
device = first_module.lora_down._memory_management_device
elif hasattr(first_module, 'lokr_w1'):
device = first_module.lokr_w1.device
dtype = first_module.lokr_w1.dtype
if hasattr(first_module.lokr_w1, '_memory_management_device'):
device = first_module.lokr_w1._memory_management_device
elif hasattr(first_module, 'lokr_w1_a'):
device = first_module.lokr_w1_a.device
dtype = first_module.lokr_w1_a.dtype
if hasattr(first_module.lokr_w1_a, '_memory_management_device'):
device = first_module.lokr_w1_a._memory_management_device
else:
raise ValueError("Unknown module type")
with torch.no_grad():