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add new VAE encoding strategy during HR fix

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cool-bigdogs-tshirt
2023-06-02 19:35:57 -05:00
parent 5f2bdba818
commit 3889e5a5b0
2 changed files with 13 additions and 1 deletions
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modules/processing.py
+12 -1
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@@ -922,7 +922,18 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
decoded_samples = torch.from_numpy(np.array(batch_images))
decoded_samples = decoded_samples.to(shared.device)
decoded_samples = 2. * decoded_samples - 1.
samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples))
if shared.opts.sd_vae_sliced_encode:
samples = torch.stack([
self.sd_model.get_first_stage_encoding(
self.sd_model.encode_first_stage(torch.unsqueeze(decoded_sample, 0))
)[0]
for decoded_sample
in decoded_samples
])
else:
samples = self.sd_model.get_first_stage_encoding(
self.sd_model.encode_first_stage(decoded_samples)
)
image_conditioning = self.img2img_image_conditioning(decoded_samples, samples)
shared.state.nextjob()
img2img_sampler_name = self.sampler_name