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author | Jim Hays <jim@emporatitle.com> | 2022-12-15 02:01:32 +0000 |
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committer | Jim Hays <jim@emporatitle.com> | 2022-12-15 02:01:32 +0000 |
commit | c0355caefe3d82e304e6d832699d581fc8f9fbf9 (patch) | |
tree | fd4289de6410ad909371225550e768e37136661e /modules/sd_hijack_inpainting.py | |
parent | 685f9631b56ff8bd43bce24ff5ce0f9a0e9af490 (diff) | |
download | stable-diffusion-webui-gfx803-c0355caefe3d82e304e6d832699d581fc8f9fbf9.tar.gz stable-diffusion-webui-gfx803-c0355caefe3d82e304e6d832699d581fc8f9fbf9.tar.bz2 stable-diffusion-webui-gfx803-c0355caefe3d82e304e6d832699d581fc8f9fbf9.zip |
Fix various typos
Diffstat (limited to 'modules/sd_hijack_inpainting.py')
-rw-r--r-- | modules/sd_hijack_inpainting.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 938f9a58..d72f83fd 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -209,7 +209,7 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F else: x_in = torch.cat([x] * 2) t_in = torch.cat([t] * 2) - + if isinstance(c, dict): assert isinstance(unconditional_conditioning, dict) c_in = dict() @@ -278,7 +278,7 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F x_prev, pred_x0 = get_x_prev_and_pred_x0(e_t_prime, index) return x_prev, pred_x0, e_t - + # ================================================================================================= # Monkey patch LatentInpaintDiffusion to load the checkpoint with a proper config. # Adapted from: @@ -326,7 +326,7 @@ def do_inpainting_hijack(): # 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 + # this file should be cleaned up later if everything turns out to work fine # ldm.models.diffusion.ddpm.get_unconditional_conditioning = get_unconditional_conditioning ldm.models.diffusion.ddpm.LatentInpaintDiffusion = LatentInpaintDiffusion |