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* mm: default to 0 for NUM_STREAMS Dont count the compute stream as an offload stream. This makes async offload accounting easier. * mm: remove 128MB minimum This is from a previous offloading system requirement. Remove it to make behaviour of the loader and partial unloader consistent. * mp: order the module list by offload expense Calculate an approximate offloading temporary VRAM cost to offload a weight and primary order the module load list by that. In the simple case this is just the same as the module weight, but with Loras, a weight with a lora consumes considerably more VRAM to do the Lora application on-the-fly. This will slightly prioritize lora weights, but is really for proper VRAM offload accounting. * mp: Account for the VRAM cost of weight offloading when checking the VRAM headroom, assume that the weight needs to be offloaded, and only load if it has space for both the load and offload * the number of streams. As the weights are ordered from largest to smallest by offload cost this is guaranteed to fit in VRAM (tm), as all weights that follow will be smaller. Make the partial unload aware of this system as well by saving the budget for offload VRAM to the model state and accounting accordingly. Its possible that partial unload increases the size of the largest offloaded weights, and thus needs to unload a little bit more than asked to accomodate the bigger temp buffers. Honor the existing codes floor on model weight loading of 128MB by having the patcher honor this separately withough regard to offloading. Otherwise when MM specifies its 128MB minimum, MP will see the biggest weights, and budget that 128MB to only offload buffer and load nothing which isnt the intent of these minimums. The same clamp applies in case of partial offload of the currently loading model. |
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| .. | ||
| audio_encoders | ||
| cldm | ||
| comfy_types | ||
| extra_samplers | ||
| image_encoders | ||
| k_diffusion | ||
| ldm | ||
| sd1_tokenizer | ||
| t2i_adapter | ||
| taesd | ||
| text_encoders | ||
| weight_adapter | ||
| checkpoint_pickle.py | ||
| cli_args.py | ||
| clip_config_bigg.json | ||
| clip_model.py | ||
| clip_vision_config_g.json | ||
| clip_vision_config_h.json | ||
| clip_vision_config_vitl_336_llava.json | ||
| clip_vision_config_vitl_336.json | ||
| clip_vision_config_vitl.json | ||
| clip_vision_siglip_384.json | ||
| clip_vision_siglip_512.json | ||
| clip_vision.py | ||
| conds.py | ||
| context_windows.py | ||
| controlnet.py | ||
| diffusers_convert.py | ||
| diffusers_load.py | ||
| float.py | ||
| gligen.py | ||
| hooks.py | ||
| latent_formats.py | ||
| lora_convert.py | ||
| lora.py | ||
| model_base.py | ||
| model_detection.py | ||
| model_management.py | ||
| model_patcher.py | ||
| model_sampling.py | ||
| nested_tensor.py | ||
| ops.py | ||
| options.py | ||
| patcher_extension.py | ||
| pixel_space_convert.py | ||
| quant_ops.py | ||
| rmsnorm.py | ||
| sample.py | ||
| sampler_helpers.py | ||
| samplers.py | ||
| sd1_clip_config.json | ||
| sd1_clip.py | ||
| sd.py | ||
| sdxl_clip.py | ||
| supported_models_base.py | ||
| supported_models.py | ||
| utils.py | ||