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| author | AUTOMATIC1111 <16777216c@gmail.com> | 2023-05-17 14:45:38 +0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-05-17 14:45:38 +0300 |
| commit | 875ccc27f626dbeafbbf358ea3623fc7d2698072 (patch) | |
| tree | dd4e23d6059744bb642c7233437d28a671275580 /modules | |
| parent | 9ac85b8b73e180154453609f10b044a475289e24 (diff) | |
| parent | 7a13a3f4ba86dc44fcf7d9944b179018744862f5 (diff) | |
Merge pull request #10467 from Sakura-Luna/taesd-a
Tiny AE fix
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/sd_samplers_common.py | 9 | ||||
| -rw-r--r-- | modules/sd_vae_taesd.py | 2 |
2 files changed, 6 insertions, 5 deletions
diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index ceda6a35..d99c933d 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -35,13 +35,14 @@ def single_sample_to_image(sample, approximation=None): elif approximation == 1:
x_sample = sd_vae_approx.model()(sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach()
elif approximation == 3:
- x_sample = sd_vae_taesd.model()(sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach()
- x_sample = sd_vae_taesd.TAESD.unscale_latents(x_sample) # returns value in [-2, 2]
- x_sample = x_sample * 0.5
+ x_sample = sample * 1.5
+ x_sample = sd_vae_taesd.model()(x_sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach()
else:
x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0]
- x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0)
+ if approximation != 3:
+ x_sample = (x_sample + 1.0) / 2.0
+ x_sample = torch.clamp(x_sample, min=0.0, max=1.0)
x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
x_sample = x_sample.astype(np.uint8)
diff --git a/modules/sd_vae_taesd.py b/modules/sd_vae_taesd.py index d23812ef..5e8496e8 100644 --- a/modules/sd_vae_taesd.py +++ b/modules/sd_vae_taesd.py @@ -45,7 +45,7 @@ def decoder(): class TAESD(nn.Module): - latent_magnitude = 2 + latent_magnitude = 3 latent_shift = 0.5 def __init__(self, decoder_path="taesd_decoder.pth"): |