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Add support Stable Diffusion 2.0

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AUTOMATIC
2022-11-26 16:10:46 +03:00
parent 828438b4a1
commit ce6911158b
15 changed files with 504 additions and 331 deletions
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20
modules/sd_hijack_inpainting.py
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@@ -199,8 +199,8 @@ def sample_plms(self,
@torch.no_grad()
def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None,
unconditional_guidance_scale=1., unconditional_conditioning=None, old_eps=None, t_next=None):
temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None,
unconditional_guidance_scale=1., unconditional_conditioning=None, old_eps=None, t_next=None, dynamic_threshold=None):
b, *_, device = *x.shape, x.device
def get_model_output(x, t):
@@ -249,6 +249,8 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F
pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt()
if quantize_denoised:
pred_x0, _, *_ = self.model.first_stage_model.quantize(pred_x0)
if dynamic_threshold is not None:
pred_x0 = norm_thresholding(pred_x0, dynamic_threshold)
# direction pointing to x_t
dir_xt = (1. - a_prev - sigma_t**2).sqrt() * e_t
noise = sigma_t * noise_like(x.shape, device, repeat_noise) * temperature
@@ -321,12 +323,16 @@ def should_hijack_inpainting(checkpoint_info):
def do_inpainting_hijack():
ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning
# most of this stuff seems to no longer be needed because it is already included into SD2.0
# LatentInpaintDiffusion remains because SD2.0's LatentInpaintDiffusion can't be loaded without specifying a checkpoint
# p_sample_plms is needed because PLMS can't work with dicts as conditionings
# this file should be cleaned up later if weverything tuens out to work fine
# ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning
ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion
ldm.models.diffusion.ddim.DDIMSampler.p_sample_ddim = p_sample_ddim
ldm.models.diffusion.ddim.DDIMSampler.sample = sample_ddim
# ldm.models.diffusion.ddim.DDIMSampler.p_sample_ddim = p_sample_ddim
# ldm.models.diffusion.ddim.DDIMSampler.sample = sample_ddim
ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms
ldm.models.diffusion.plms.PLMSSampler.sample = sample_plms
# ldm.models.diffusion.plms.PLMSSampler.sample = sample_plms