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Auto calculate amount of memory to use for --lowvram

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comfyanonymous 2023-02-08 11:42:37 -05:00
parent 534736b924
commit c92633eaa2
1 changed files with 10 additions and 1 deletions
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11
comfy/model_management.py
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@ -7,6 +7,8 @@ NORMAL_VRAM = 3
accelerate_enabled = False accelerate_enabled = False
vram_state = NORMAL_VRAM vram_state = NORMAL_VRAM
total_vram_available_mb = -1
import sys import sys
set_vram_to = NORMAL_VRAM set_vram_to = NORMAL_VRAM
@ -24,6 +26,13 @@ if set_vram_to != NORMAL_VRAM:
import traceback import traceback
print(traceback.format_exc()) print(traceback.format_exc())
print("ERROR: COULD NOT ENABLE LOW VRAM MODE.") print("ERROR: COULD NOT ENABLE LOW VRAM MODE.")
try:
import torch
total_vram_available_mb = torch.cuda.mem_get_info(torch.cuda.current_device())[1] / (1024 * 1024)
except:
pass
total_vram_available_mb = (total_vram_available_mb - 1024) // 2
total_vram_available_mb = int(max(256, total_vram_available_mb))
print("Set vram state to:", ["CPU", "NO VRAM", "LOW VRAM", "NORMAL VRAM"][vram_state]) print("Set vram state to:", ["CPU", "NO VRAM", "LOW VRAM", "NORMAL VRAM"][vram_state])
@ -71,7 +80,7 @@ def load_model_gpu(model):
if vram_state == NO_VRAM: if vram_state == NO_VRAM:
device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "256MiB", "cpu": "16GiB"}) device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "256MiB", "cpu": "16GiB"})
elif vram_state == LOW_VRAM: elif vram_state == LOW_VRAM:
device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "1GiB", "cpu": "16GiB"}) device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "{}MiB".format(total_vram_available_mb), "cpu": "16GiB"})
accelerate.dispatch_model(real_model, device_map=device_map, main_device="cuda") accelerate.dispatch_model(real_model, device_map=device_map, main_device="cuda")
model_accelerated = True model_accelerated = True
return current_loaded_model return current_loaded_model