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bring back scale latent option in settings

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AUTOMATIC
2022-10-15 13:23:12 +03:00
parent 5967d07d1a
commit f7ca63937a
2 changed files with 6 additions and 5 deletions
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8
modules/processing.py
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@@ -557,11 +557,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
samples = samples[:, :, self.truncate_y//2:samples.shape[2]-self.truncate_y//2, self.truncate_x//2:samples.shape[3]-self.truncate_x//2]
decoded_samples = decode_first_stage(self.sd_model, samples)
if opts.use_scale_latent_for_hires_fix:
samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None":
decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear")
else:
decoded_samples = decode_first_stage(self.sd_model, samples)
lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0)
batch_images = []
@@ -578,7 +578,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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))
samples = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(decoded_samples))
shared.state.nextjob()