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feat: add cpu_offload option for low-VRAM model loading #40

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feat: add cpu_offload option for low-VRAM model loading #40

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20 changes: 15 additions & 5 deletions src/world_engine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,13 +41,15 @@ def __init__(
model_config_overrides: Optional[Dict] = None,
device=None,
dtype=torch.bfloat16,
load_weights: bool = True
load_weights: bool = True,
cpu_offload: bool = False,
):
"""
model_uri: HF URI or local folder containing model.safetensors and config.yaml
quant: None | intw8a8 | fp8w8a8 | nvfp4
model_config_overrides: Dict to override model config values
- auto_aspect_ratio: set to False to work in ae raw space, otherwise in/out are 720p or 360p
cpu_offload: build model on CPU before moving to GPU (reduces peak VRAM)
"""
self.device = torch.get_default_device() if device is None else device
self.dtype = torch.get_default_dtype() if dtype is None else dtype
Expand Down Expand Up @@ -76,10 +78,18 @@ def __init__(
if self.model_cfg.prompt_conditioning is not None:
self.prompt_encoder = PromptEncoder(self.model_cfg.prompt_encoder_uri, dtype=dtype).eval()

self.model = WorldModel.from_pretrained(
model_uri, cfg=self.model_cfg, device=self.device, dtype=dtype, load_weights=load_weights
).eval()
apply_inference_patches(self.model)
if cpu_offload and str(self.device) != "cpu":
with torch.device("cpu"):
self.model = WorldModel.from_pretrained(
model_uri, cfg=self.model_cfg, device="cpu", dtype=dtype, load_weights=load_weights
).eval()
apply_inference_patches(self.model)
self.model = self.model.to(self.device)
else:
self.model = WorldModel.from_pretrained(
model_uri, cfg=self.model_cfg, device=self.device, dtype=dtype, load_weights=load_weights
).eval()
apply_inference_patches(self.model)
if quant is not None:
quantize_model(self.model, quant)

Expand Down