From c0355caefe3d82e304e6d832699d581fc8f9fbf9 Mon Sep 17 00:00:00 2001 From: Jim Hays Date: Wed, 14 Dec 2022 21:01:32 -0500 Subject: Fix various typos --- modules/processing.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index 24c537d1..fe7f4faf 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -147,11 +147,11 @@ class StableDiffusionProcessing(): # The "masked-image" in this case will just be all zeros since the entire image is masked. image_conditioning = torch.zeros(x.shape[0], 3, height, width, device=x.device) - image_conditioning = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image_conditioning)) + image_conditioning = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image_conditioning)) # Add the fake full 1s mask to the first dimension. image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0) - image_conditioning = image_conditioning.to(x.dtype) + image_conditioning = image_conditioning.to(x.dtype) return image_conditioning @@ -199,7 +199,7 @@ class StableDiffusionProcessing(): source_image * (1.0 - conditioning_mask), getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) ) - + # Encode the new masked image using first stage of network. conditioning_image = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(conditioning_image)) @@ -537,7 +537,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: for n in range(p.n_iter): if state.skipped: state.skipped = False - + if state.interrupted: break @@ -612,7 +612,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: image.info["parameters"] = text output_images.append(image) - del x_samples_ddim + del x_samples_ddim devices.torch_gc() @@ -704,7 +704,7 @@ 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] - """saves image before applying hires fix, if enabled in options; takes as an arguyment either an image or batch with latent space images""" + """saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images""" def save_intermediate(image, index): if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix: return @@ -720,7 +720,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear") - # Avoid making the inpainting conditioning unless necessary as + # Avoid making the inpainting conditioning unless necessary as # this does need some extra compute to decode / encode the image again. if getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) < 1.0: image_conditioning = self.img2img_image_conditioning(decode_first_stage(self.sd_model, samples), samples) -- cgit v1.2.1