alphard/efficiency-nodes-comfyui
1
0
Fork 0
mirror of https://github.com/jags111/efficiency-nodes-comfyui.git synced 2026-03-21 21:22:13 -03:00
Code Issues Packages Projects Releases Wiki Activity

Fix the error of model.device being undefined on macOS (#267)

Browse Source
This commit is contained in:
Akuma
2025-04-02 16:38:25 +08:00
committed by GitHub
parent 11effed8d1
commit 490f749c37
1 changed files with 6 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
py/bnk_tiled_samplers.py
View File

@@ -20,6 +20,9 @@ MAX_RESOLUTION=8192
####################### #######################
def get_device():
return comfy.model_management.get_torch_device()
def recursion_to_list(obj, attr): def recursion_to_list(obj, attr):
current = obj current = obj
yield current yield current
@@ -86,13 +89,13 @@ def slice_gligen(tile_h, tile_h_len, tile_w, tile_w_len, cond, gligen):
def slice_cnet(h, h_len, w, w_len, model:comfy.controlnet.ControlBase, img): def slice_cnet(h, h_len, w, w_len, model:comfy.controlnet.ControlBase, img):
if img is None: if img is None:
img = model.cond_hint_original img = model.cond_hint_original
model.cond_hint = tiling.get_slice(img, h*8, h_len*8, w*8, w_len*8).to(model.control_model.dtype).to(model.device) model.cond_hint = tiling.get_slice(img, h*8, h_len*8, w*8, w_len*8).to(model.control_model.dtype).to(get_device())
def slices_T2I(h, h_len, w, w_len, model:comfy.controlnet.ControlBase, img): def slices_T2I(h, h_len, w, w_len, model:comfy.controlnet.ControlBase, img):
model.control_input = None model.control_input = None
if img is None: if img is None:
img = model.cond_hint_original img = model.cond_hint_original
model.cond_hint = tiling.get_slice(img, h*8, h_len*8, w*8, w_len*8).float().to(model.device) model.cond_hint = tiling.get_slice(img, h*8, h_len*8, w*8, w_len*8).float().to(get_device())
# TODO: refactor some of the mess # TODO: refactor some of the mess
@@ -100,7 +103,7 @@ from PIL import Image
def sample_common(model, add_noise, noise_seed, tile_width, tile_height, tiling_strategy, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0, preview=False): def sample_common(model, add_noise, noise_seed, tile_width, tile_height, tiling_strategy, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0, preview=False):
end_at_step = min(end_at_step, steps) end_at_step = min(end_at_step, steps)
device = comfy.model_management.get_torch_device() device = get_device()
samples = latent_image["samples"] samples = latent_image["samples"]
noise_mask = latent_image["noise_mask"] if "noise_mask" in latent_image else None noise_mask = latent_image["noise_mask"] if "noise_mask" in latent_image else None
force_full_denoise = return_with_leftover_noise == "enable" force_full_denoise = return_with_leftover_noise == "enable"