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Make sure cond_concat is on the right device.

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comfyanonymous 2023-10-19 01:10:41 -04:00
parent 45c972aba8
commit e6962120c6
2 changed files with 7 additions and 5 deletions
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5
comfy/model_base.py
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@ -79,6 +79,7 @@ class BaseModel(torch.nn.Module):
denoise_mask = kwargs.get("denoise_mask", None) denoise_mask = kwargs.get("denoise_mask", None)
latent_image = kwargs.get("latent_image", None) latent_image = kwargs.get("latent_image", None)
noise = kwargs.get("noise", None) noise = kwargs.get("noise", None)
device = kwargs["device"]
def blank_inpaint_image_like(latent_image): def blank_inpaint_image_like(latent_image):
blank_image = torch.ones_like(latent_image) blank_image = torch.ones_like(latent_image)
@ -92,9 +93,9 @@ class BaseModel(torch.nn.Module):
for ck in concat_keys: for ck in concat_keys:
if denoise_mask is not None: if denoise_mask is not None:
if ck == "mask": if ck == "mask":
cond_concat.append(denoise_mask[:,:1]) cond_concat.append(denoise_mask[:,:1].to(device))
elif ck == "masked_image": elif ck == "masked_image":
cond_concat.append(latent_image) #NOTE: the latent_image should be masked by the mask in pixel space cond_concat.append(latent_image.to(device)) #NOTE: the latent_image should be masked by the mask in pixel space
else: else:
if ck == "mask": if ck == "mask":
cond_concat.append(torch.ones_like(noise)[:,:1]) cond_concat.append(torch.ones_like(noise)[:,:1])

7
comfy/samplers.py
View File

@ -537,10 +537,11 @@ def encode_adm(model, conds, batch_size, width, height, device, prompt_type):
return conds return conds
def encode_cond(model_function, key, conds, **kwargs): def encode_cond(model_function, key, conds, device, **kwargs):
for t in range(len(conds)): for t in range(len(conds)):
x = conds[t] x = conds[t]
params = x[1].copy() params = x[1].copy()
params["device"] = device
for k in kwargs: for k in kwargs:
if k not in params: if k not in params:
params[k] = kwargs[k] params[k] = kwargs[k]
@ -677,8 +678,8 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model
negative = encode_adm(model, negative, noise.shape[0], noise.shape[3], noise.shape[2], device, "negative") negative = encode_adm(model, negative, noise.shape[0], noise.shape[3], noise.shape[2], device, "negative")
if hasattr(model, 'cond_concat'): if hasattr(model, 'cond_concat'):
positive = encode_cond(model.cond_concat, "concat", positive, noise=noise, latent_image=latent_image, denoise_mask=denoise_mask) positive = encode_cond(model.cond_concat, "concat", positive, device, noise=noise, latent_image=latent_image, denoise_mask=denoise_mask)
negative = encode_cond(model.cond_concat, "concat", negative, noise=noise, latent_image=latent_image, denoise_mask=denoise_mask) negative = encode_cond(model.cond_concat, "concat", negative, device, noise=noise, latent_image=latent_image, denoise_mask=denoise_mask)
extra_args = {"cond":positive, "uncond":negative, "cond_scale": cfg, "model_options": model_options, "seed":seed} extra_args = {"cond":positive, "uncond":negative, "cond_scale": cfg, "model_options": model_options, "seed":seed}