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Add option to disable normalize embeddings after after calculating emphasis. #14874

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Merged
merged 5 commits into from
Feb 11, 2024
Merged

Add option to disable normalize embeddings after after calculating emphasis. #14874

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6b97958
Fix model switch bug
hako-mikan Nov 9, 2023
816096e
Merge branch 'dev' into master
hako-mikan Nov 9, 2023
0bc7867
Merge branch 'AUTOMATIC1111:master' into master
hako-mikan Feb 9, 2024
6b3f703
add option
hako-mikan Feb 9, 2024
c3c88ca
Update sd_hijack_clip.py
hako-mikan Feb 9, 2024
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4 changes: 3 additions & 1 deletion modules/sd_hijack_clip.py
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Expand Up @@ -279,7 +279,9 @@ def process_tokens(self, remade_batch_tokens, batch_multipliers):
original_mean = z.mean()
z = z * batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
new_mean = z.mean()
z = z * (original_mean / new_mean)

if not getattr(opts, "disable_normalize_embeddings", False):
z = z * (original_mean / new_mean)

if pooled is not None:
z.pooled = pooled
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1 change: 1 addition & 0 deletions modules/shared_options.py
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Expand Up @@ -150,6 +150,7 @@
"sd_unet": OptionInfo("Automatic", "SD Unet", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list).info("choose Unet model: Automatic = use one with same filename as checkpoint; None = use Unet from checkpoint"),
"enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_reload_ui(),
"enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"),
"disable_normalize_embeddings": OptionInfo(False, "Disable normalize embeddings").info("Do not normalize embeddings after calculating emphasis. It can be expected to be effective in preventing artifacts in SDXL."),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"),
"CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}, infotext="Clip skip").link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"),
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