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Merge branch 'comfyanonymous:master' into feature/preview-latent

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Dr.Lt.Data 2023-06-19 00:52:52 +09:00 committed by GitHub
commit 2ff593b2c6
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2 changed files with 2 additions and 5 deletions
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4
comfy/ldm/models/diffusion/ddim.py
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@ -284,7 +284,7 @@ class DDIMSampler(object):
model_output = model_uncond + unconditional_guidance_scale * (model_t - model_uncond)
if self.model.parameterization == "v":
e_t = self.model.predict_eps_from_z_and_v(x, t, model_output)
e_t = extract_into_tensor(self.sqrt_alphas_cumprod, t, x.shape) * model_output + extract_into_tensor(self.sqrt_one_minus_alphas_cumprod, t, x.shape) * x
else:
e_t = model_output
@ -306,7 +306,7 @@ class DDIMSampler(object):
if self.model.parameterization != "v":
pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt()
else:
pred_x0 = self.model.predict_start_from_z_and_v(x, t, model_output)
pred_x0 = extract_into_tensor(self.sqrt_alphas_cumprod, t, x.shape) * x - extract_into_tensor(self.sqrt_one_minus_alphas_cumprod, t, x.shape) * model_output
if quantize_denoised:
pred_x0, _, *_ = self.model.first_stage_model.quantize(pred_x0)

3
comfy/sd.py
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@ -1159,9 +1159,6 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o
else:
model = model_base.BaseModel(unet_config, v_prediction=v_prediction)
if fp16:
model = model.half()
model = load_model_weights(model, sd, verbose=False, load_state_dict_to=load_state_dict_to)
return (ModelPatcher(model), clip, vae, clipvision)