diff options
Diffstat (limited to 'modules/processing.py')
| -rw-r--r-- | modules/processing.py | 12 |
1 files changed, 9 insertions, 3 deletions
diff --git a/modules/processing.py b/modules/processing.py index 43cb763f..a9d66005 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -795,7 +795,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if getattr(samples_ddim, 'already_decoded', False):
x_samples_ddim = samples_ddim
else:
- p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method
+ if opts.sd_vae_decode_method != 'Full':
+ p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method
+
x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True)
x_samples_ddim = torch.stack(x_samples_ddim).float()
@@ -1138,7 +1140,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): decoded_samples = torch.from_numpy(np.array(batch_images))
decoded_samples = decoded_samples.to(shared.device, dtype=devices.dtype_vae)
- self.extra_generation_params['VAE Encoder'] = opts.sd_vae_encode_method
+ if opts.sd_vae_encode_method != 'Full':
+ self.extra_generation_params['VAE Encoder'] = opts.sd_vae_encode_method
samples = images_tensor_to_samples(decoded_samples, approximation_indexes.get(opts.sd_vae_encode_method))
image_conditioning = self.img2img_image_conditioning(decoded_samples, samples)
@@ -1375,7 +1378,10 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): image = torch.from_numpy(batch_images)
image = image.to(shared.device, dtype=devices.dtype_vae)
- self.extra_generation_params['VAE Encoder'] = opts.sd_vae_encode_method
+
+ if opts.sd_vae_encode_method != 'Full':
+ self.extra_generation_params['VAE Encoder'] = opts.sd_vae_encode_method
+
self.init_latent = images_tensor_to_samples(image, approximation_indexes.get(opts.sd_vae_encode_method), self.sd_model)
devices.torch_gc()
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