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[WIP][LoRA] Implement hot-swapping of LoRA #9453

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[WIP][LoRA] Implement hot-swapping of LoRA #9453

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d3fbd7b
[WIP][LoRA] Implement hot-swapping of LoRA
BenjaminBossan Sep 17, 2024
84bae62
Reviewer feedback
BenjaminBossan Sep 18, 2024
63ece9d
Reviewer feedback, adjust test
BenjaminBossan Oct 16, 2024
94c669c
Merge branch 'main' into lora-hot-swapping
BenjaminBossan Oct 16, 2024
c7378ed
Fix, doc
BenjaminBossan Oct 16, 2024
7c67b38
Make fix
BenjaminBossan Oct 16, 2024
ea12e0d
Fix for possible g++ error
BenjaminBossan Oct 16, 2024
ec4b0d5
Add test for recompilation w/o hotswapping
BenjaminBossan Oct 18, 2024
e07323a
Merge branch 'main' into lora-hot-swapping
sayakpaul Oct 18, 2024
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86 changes: 69 additions & 17 deletions src/diffusers/loaders/lora_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -77,7 +77,11 @@ class StableDiffusionLoraLoaderMixin(LoraBaseMixin):
text_encoder_name = TEXT_ENCODER_NAME

def load_lora_weights(
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Just a note to the reviewers that we're currently only brainstorming the changes through unet. Those changes will be propagated to lora_pipeline.py, too once we agree on the initial design.

self, pretrained_model_name_or_path_or_dict: Union[str, Dict[str, torch.Tensor]], adapter_name=None, **kwargs
self,
pretrained_model_name_or_path_or_dict: Union[str, Dict[str, torch.Tensor]],
adapter_name=None,
hotswap: bool = False,
**kwargs,
):
"""
Load LoRA weights specified in `pretrained_model_name_or_path_or_dict` into `self.unet` and
Expand All @@ -103,6 +107,7 @@ def load_lora_weights(
low_cpu_mem_usage (`bool`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
hotswap TODO
kwargs (`dict`, *optional*):
See [`~loaders.StableDiffusionLoraLoaderMixin.lora_state_dict`].
"""
Expand Down Expand Up @@ -133,6 +138,7 @@ def load_lora_weights(
adapter_name=adapter_name,
_pipeline=self,
low_cpu_mem_usage=low_cpu_mem_usage,
hotswap=hotswap,
)
self.load_lora_into_text_encoder(
state_dict,
Expand Down Expand Up @@ -263,7 +269,14 @@ def lora_state_dict(

@classmethod
def load_lora_into_unet(
cls, state_dict, network_alphas, unet, adapter_name=None, _pipeline=None, low_cpu_mem_usage=False
cls,
state_dict,
network_alphas,
unet,
adapter_name=None,
_pipeline=None,
low_cpu_mem_usage=False,
hotswap: bool = False,
):
"""
This will load the LoRA layers specified in `state_dict` into `unet`.
Expand All @@ -282,7 +295,10 @@ def load_lora_into_unet(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading only loading the pretrained LoRA weights and not initializing the random weights.
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
hotswap TODO
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand All @@ -306,6 +322,7 @@ def load_lora_into_unet(
adapter_name=adapter_name,
_pipeline=_pipeline,
low_cpu_mem_usage=low_cpu_mem_usage,
hotswap=hotswap,
)

@classmethod
Expand Down Expand Up @@ -341,7 +358,9 @@ def load_lora_into_text_encoder(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand Down Expand Up @@ -601,7 +620,9 @@ def load_lora_weights(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
kwargs (`dict`, *optional*):
See [`~loaders.StableDiffusionLoraLoaderMixin.lora_state_dict`].
"""
Expand Down Expand Up @@ -786,7 +807,14 @@ def lora_state_dict(
@classmethod
# Copied from diffusers.loaders.lora_pipeline.StableDiffusionLoraLoaderMixin.load_lora_into_unet
def load_lora_into_unet(
cls, state_dict, network_alphas, unet, adapter_name=None, _pipeline=None, low_cpu_mem_usage=False
cls,
state_dict,
network_alphas,
unet,
adapter_name=None,
_pipeline=None,
low_cpu_mem_usage=False,
hotswap: bool = False,
):
"""
This will load the LoRA layers specified in `state_dict` into `unet`.
Expand All @@ -805,7 +833,10 @@ def load_lora_into_unet(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading only loading the pretrained LoRA weights and not initializing the random weights.
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
hotswap TODO
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand All @@ -829,6 +860,7 @@ def load_lora_into_unet(
adapter_name=adapter_name,
_pipeline=_pipeline,
low_cpu_mem_usage=low_cpu_mem_usage,
hotswap=hotswap,
)

@classmethod
Expand Down Expand Up @@ -865,7 +897,9 @@ def load_lora_into_text_encoder(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand Down Expand Up @@ -1226,7 +1260,9 @@ def load_lora_weights(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
kwargs (`dict`, *optional*):
See [`~loaders.StableDiffusionLoraLoaderMixin.lora_state_dict`].
"""
Expand Down Expand Up @@ -1301,7 +1337,9 @@ def load_lora_into_transformer(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if low_cpu_mem_usage and is_peft_version("<", "0.13.0"):
raise ValueError(
Expand Down Expand Up @@ -1424,7 +1462,9 @@ def load_lora_into_text_encoder(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand Down Expand Up @@ -1819,7 +1859,9 @@ def load_lora_weights(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand Down Expand Up @@ -1886,7 +1928,9 @@ def load_lora_into_transformer(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if low_cpu_mem_usage and not is_peft_version(">=", "0.13.1"):
raise ValueError(
Expand Down Expand Up @@ -2014,7 +2058,9 @@ def load_lora_into_text_encoder(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand Down Expand Up @@ -2377,7 +2423,9 @@ def load_lora_into_text_encoder(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if not USE_PEFT_BACKEND:
raise ValueError("PEFT backend is required for this method.")
Expand Down Expand Up @@ -2658,7 +2706,9 @@ def load_lora_weights(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
kwargs (`dict`, *optional*):
See [`~loaders.StableDiffusionLoraLoaderMixin.lora_state_dict`].
"""
Expand Down Expand Up @@ -2708,7 +2758,9 @@ def load_lora_into_transformer(
adapter_name (`str`, *optional*):
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
`default_{i}` where i is the total number of adapters being loaded.
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random weights.:
low_cpu_mem_usage (`boo`, *optional*):
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.
"""
if low_cpu_mem_usage and is_peft_version("<", "0.13.0"):
raise ValueError(
Expand Down
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