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option - sd
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Haoming
parent
94e9305aaa
commit
aa1db73b44
@ -25,12 +25,12 @@ class Emphasis:
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class EmphasisNone(Emphasis):
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name = "None"
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description = "disable the mechanism entirely and treat (:.1.1) as literal characters"
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description = "disable Emphasis entirely and treat (:1.2) as literal characters"
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class EmphasisIgnore(Emphasis):
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name = "Ignore"
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description = "treat all empasised words as if they have no emphasis"
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description = "treat all words as if they have no emphasis"
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class EmphasisOriginal(Emphasis):
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@ -48,7 +48,7 @@ class EmphasisOriginal(Emphasis):
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class EmphasisOriginalNoNorm(EmphasisOriginal):
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name = "No norm"
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description = "same as original, but without normalization (seems to work better for SDXL)"
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description = "implementation without normalization (fix certain issues for SDXL)"
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def after_transformers(self):
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self.z = self.z * self.multipliers.reshape(self.multipliers.shape + (1,)).expand(self.z.shape)
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@ -59,7 +59,11 @@ def get_current_option(emphasis_option_name):
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def get_options_descriptions():
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return ", ".join(f"{x.name}: {x.description}" for x in options)
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return f"""
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<ul style='margin-left: 1.5em'><li>
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{"</li><li>".join(f"<b>{x.name}</b>: {x.description}" for x in options)}
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</li></ul>
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"""
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options = [
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@ -199,32 +199,18 @@ options_templates.update(
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("sd", "Stable Diffusion", "sd"),
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{
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"sd_model_checkpoint": OptionInfo(None, "(Managed by Forge)", gr.State, infotext="Model"),
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"sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}),
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"sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"),
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"sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"),
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"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"),
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"enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_reload_ui(),
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"emphasis": OptionInfo("Original", "Emphasis mode", gr.Radio, lambda: {"choices": [x.name for x in sd_emphasis.options]}, infotext="Emphasis").info("makes it possible to make model to pay (more:1.1) or (less:0.9) attention to text when you use the syntax in prompt; " + sd_emphasis.get_options_descriptions()),
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"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
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"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"),
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"sdxl_clip_l_skip": OptionInfo(False, "Clip skip SDXL", gr.Checkbox).info("Enable Clip skip for the secondary clip model in sdxl. Has no effect on SD 1.5 or SD 2.0/2.1."),
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"CLIP_stop_at_last_layers": OptionInfo(1, "(Managed by Forge)", gr.State, infotext="Clip skip"),
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"upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
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"randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}, infotext="RNG").info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"),
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"tiling": OptionInfo(False, "Tiling", infotext="Tiling").info("produce a tileable picture"),
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"hires_fix_refiner_pass": OptionInfo("second pass", "Hires fix: which pass to enable refiner for", gr.Radio, {"choices": ["first pass", "second pass", "both passes"]}, infotext="Hires refiner"),
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},
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)
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)
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options_templates.update(
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options_section(
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("sdxl", "Stable Diffusion XL", "sd"),
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{
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"sdxl_crop_top": OptionInfo(0, "crop top coordinate", gr.Number, {"minimum": 0, "maximum": 1024, "step": 1}),
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"sdxl_crop_left": OptionInfo(0, "crop left coordinate", gr.Number, {"minimum": 0, "maximum": 1024, "step": 1}),
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"sdxl_refiner_low_aesthetic_score": OptionInfo(2.5, "SDXL low aesthetic score", gr.Slider, {"minimum": 0, "maximum": 10, "step": 0.1}).info("used for refiner model negative prompt"),
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"sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "SDXL high aesthetic score", gr.Slider, {"minimum": 0, "maximum": 10, "step": 0.1}).info("used for refiner model prompt"),
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"sd_unet": OptionInfo("Automatic", "SD UNet", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list),
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"emphasis": OptionInfo("Original", "Emphasis Mode", gr.Radio, lambda: {"choices": [x.name for x in sd_emphasis.options]}, infotext="Emphasis").info("pay (more:1.1) or (less:0.9) attention to prompts").html(sd_emphasis.get_options_descriptions()),
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"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("1 = disable, 2 = skip one layer, etc."),
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"comma_padding_backtrack": OptionInfo(16, "Token Wrap Length", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("for prompts shorter than the threshold, move them to the next chunk of 75 tokens if they do not fit inside the current chunk"),
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"tiling": OptionInfo(False, "Tiling", infotext="Tiling").info("produce a tileable image"),
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"hires_fix_refiner_pass": OptionInfo("second pass", "Which pass during Hires. fix to enable Refiner", gr.Radio, {"choices": ("first pass", "second pass", "both passes")}, infotext="Hires refiner"),
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"randn_source": OptionInfo("CPU", "Random Number Generator", gr.Radio, {"choices": ("CPU", "GPU", "NV")}, infotext="RNG").info("use <b>CPU</b> for the maximum recreatability across different systems"),
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"divxl": OptionDiv(),
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"sdxl_crop_top": OptionInfo(0, "[SDXL] Crop-Top Coordinate"),
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"sdxl_crop_left": OptionInfo(0, "[SDXL] Crop-Left Coordinate"),
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"sdxl_refiner_low_aesthetic_score": OptionInfo(2.5, "[SDXL] Low Aesthetic Score", gr.Number),
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"sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "[SDXL] High Aesthetic Score", gr.Number),
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},
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)
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)
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