Compare commits
11 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 3690e4e82c | |||
| 6427ffde4d | |||
| c63d46ceb8 | |||
| fae8bdfa48 | |||
| 10dbee0d59 | |||
| 20ae71faa8 | |||
| 6095ade147 | |||
| dd377637ca | |||
| 50906bf78b | |||
| b186045fee | |||
| 3f50b7d71c |
+1
-1
@@ -1,4 +1,4 @@
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## Upcoming 1.3.0
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## 1.3.0
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### Features:
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### Features:
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* add UI to edit defaults
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* add UI to edit defaults
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@@ -26,7 +26,7 @@ class ExtraNetworkParams:
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self.named = {}
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self.named = {}
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for item in self.items:
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for item in self.items:
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parts = item.split('=', 2)
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parts = item.split('=', 2) if isinstance(item, str) else [item]
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if len(parts) == 2:
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if len(parts) == 2:
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self.named[parts[0]] = parts[1]
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self.named[parts[0]] = parts[1]
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else:
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else:
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@@ -35,7 +35,7 @@ def reset():
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def quote(text):
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def quote(text):
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if ',' not in str(text) and '\n' not in str(text):
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if ',' not in str(text) and '\n' not in str(text) and ':' not in str(text):
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return text
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return text
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return json.dumps(text, ensure_ascii=False)
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return json.dumps(text, ensure_ascii=False)
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+6
-3
@@ -493,9 +493,12 @@ def save_image_with_geninfo(image, geninfo, filename, extension=None, existing_p
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existing_pnginfo['parameters'] = geninfo
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existing_pnginfo['parameters'] = geninfo
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if extension.lower() == '.png':
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if extension.lower() == '.png':
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pnginfo_data = PngImagePlugin.PngInfo()
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if opts.enable_pnginfo:
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for k, v in (existing_pnginfo or {}).items():
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pnginfo_data = PngImagePlugin.PngInfo()
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pnginfo_data.add_text(k, str(v))
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for k, v in (existing_pnginfo or {}).items():
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pnginfo_data.add_text(k, str(v))
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else:
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pnginfo_data = None
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image.save(filename, format=image_format, quality=opts.jpeg_quality, pnginfo=pnginfo_data)
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image.save(filename, format=image_format, quality=opts.jpeg_quality, pnginfo=pnginfo_data)
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@@ -321,14 +321,13 @@ class StableDiffusionProcessing:
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have been used before. The second element is where the previously
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have been used before. The second element is where the previously
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computed result is stored.
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computed result is stored.
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"""
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"""
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if cache[0] is not None and (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info) == cache[0]:
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if cache[0] is not None and (required_prompts, steps) == cache[0]:
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return cache[1]
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return cache[1]
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with devices.autocast():
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with devices.autocast():
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cache[1] = function(shared.sd_model, required_prompts, steps)
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cache[1] = function(shared.sd_model, required_prompts, steps)
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cache[0] = (required_prompts, steps)
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cache[0] = (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info)
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return cache[1]
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return cache[1]
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def setup_conds(self):
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def setup_conds(self):
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+15
-6
@@ -48,6 +48,11 @@ def apply_optimizations():
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undo_optimizations()
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undo_optimizations()
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if len(optimizers) == 0:
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# a script can access the model very early, and optimizations would not be filled by then
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current_optimizer = None
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return ''
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ldm.modules.diffusionmodules.model.nonlinearity = silu
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ldm.modules.diffusionmodules.model.nonlinearity = silu
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ldm.modules.diffusionmodules.openaimodel.th = sd_hijack_unet.th
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ldm.modules.diffusionmodules.openaimodel.th = sd_hijack_unet.th
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@@ -67,8 +72,9 @@ def apply_optimizations():
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matching_optimizer = optimizers[0]
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matching_optimizer = optimizers[0]
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if matching_optimizer is not None:
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if matching_optimizer is not None:
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print(f"Applying optimization: {matching_optimizer.name}")
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print(f"Applying optimization: {matching_optimizer.name}... ", end='')
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matching_optimizer.apply()
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matching_optimizer.apply()
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print("done.")
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current_optimizer = matching_optimizer
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current_optimizer = matching_optimizer
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return current_optimizer.name
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return current_optimizer.name
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else:
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else:
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@@ -149,6 +155,13 @@ class StableDiffusionModelHijack:
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def __init__(self):
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def __init__(self):
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self.embedding_db.add_embedding_dir(cmd_opts.embeddings_dir)
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self.embedding_db.add_embedding_dir(cmd_opts.embeddings_dir)
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def apply_optimizations(self):
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try:
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self.optimization_method = apply_optimizations()
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except Exception as e:
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errors.display(e, "applying cross attention optimization")
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undo_optimizations()
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def hijack(self, m):
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def hijack(self, m):
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if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:
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if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:
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model_embeddings = m.cond_stage_model.roberta.embeddings
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model_embeddings = m.cond_stage_model.roberta.embeddings
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@@ -168,11 +181,7 @@ class StableDiffusionModelHijack:
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if m.cond_stage_key == "edit":
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if m.cond_stage_key == "edit":
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sd_hijack_unet.hijack_ddpm_edit()
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sd_hijack_unet.hijack_ddpm_edit()
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try:
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self.apply_optimizations()
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self.optimization_method = apply_optimizations()
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except Exception as e:
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errors.display(e, "applying cross attention optimization")
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undo_optimizations()
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self.clip = m.cond_stage_model
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self.clip = m.cond_stage_model
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+2
-2
@@ -505,10 +505,10 @@ def create_ui():
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with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
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with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container:
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with gr.Column(scale=80):
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with gr.Column(scale=80):
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with gr.Row():
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with gr.Row():
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hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"])
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hr_prompt = gr.Textbox(label="Hires prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"])
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with gr.Column(scale=80):
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with gr.Column(scale=80):
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with gr.Row():
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with gr.Row():
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hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"])
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hr_negative_prompt = gr.Textbox(label="Hires negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"])
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elif category == "batch":
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elif category == "batch":
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if not opts.dimensions_and_batch_together:
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if not opts.dimensions_and_batch_together:
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@@ -3,7 +3,7 @@ import tempfile
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from collections import namedtuple
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from collections import namedtuple
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from pathlib import Path
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from pathlib import Path
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import gradio as gr
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import gradio.components
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from PIL import PngImagePlugin
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from PIL import PngImagePlugin
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@@ -31,13 +31,16 @@ def check_tmp_file(gradio, filename):
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return False
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return False
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def save_pil_to_file(pil_image, dir=None):
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def save_pil_to_file(self, pil_image, dir=None):
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already_saved_as = getattr(pil_image, 'already_saved_as', None)
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already_saved_as = getattr(pil_image, 'already_saved_as', None)
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if already_saved_as and os.path.isfile(already_saved_as):
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if already_saved_as and os.path.isfile(already_saved_as):
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register_tmp_file(shared.demo, already_saved_as)
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register_tmp_file(shared.demo, already_saved_as)
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filename = already_saved_as
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file_obj = Savedfile(f'{already_saved_as}?{os.path.getmtime(already_saved_as)}')
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if not shared.opts.save_images_add_number:
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return file_obj
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filename += f'?{os.path.getmtime(already_saved_as)}'
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return filename
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if shared.opts.temp_dir != "":
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if shared.opts.temp_dir != "":
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dir = shared.opts.temp_dir
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dir = shared.opts.temp_dir
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@@ -51,11 +54,11 @@ def save_pil_to_file(pil_image, dir=None):
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file_obj = tempfile.NamedTemporaryFile(delete=False, suffix=".png", dir=dir)
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file_obj = tempfile.NamedTemporaryFile(delete=False, suffix=".png", dir=dir)
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pil_image.save(file_obj, pnginfo=(metadata if use_metadata else None))
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pil_image.save(file_obj, pnginfo=(metadata if use_metadata else None))
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return file_obj
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return file_obj.name
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# override save to file function so that it also writes PNG info
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# override save to file function so that it also writes PNG info
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gr.processing_utils.save_pil_to_file = save_pil_to_file
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gradio.components.IOComponent.pil_to_temp_file = save_pil_to_file
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def on_tmpdir_changed():
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def on_tmpdir_changed():
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@@ -756,13 +756,22 @@ footer {
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.extra-network-cards .card .metadata-button, .extra-network-thumbs .card .metadata-button{
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.extra-network-cards .card .metadata-button, .extra-network-thumbs .card .metadata-button{
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display: none;
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display: none;
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position: absolute;
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position: absolute;
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right: 0;
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color: white;
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color: white;
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right: 0;
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}
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.extra-network-cards .card .metadata-button {
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text-shadow: 2px 2px 3px black;
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text-shadow: 2px 2px 3px black;
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padding: 0.25em;
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padding: 0.25em;
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font-size: 22pt;
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font-size: 22pt;
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width: 1.5em;
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width: 1.5em;
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}
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}
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.extra-network-thumbs .card .metadata-button {
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text-shadow: 1px 1px 2px black;
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padding: 0;
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font-size: 16pt;
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width: 1em;
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top: -0.25em;
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}
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.extra-network-cards .card:hover .metadata-button, .extra-network-thumbs .card:hover .metadata-button{
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.extra-network-cards .card:hover .metadata-button, .extra-network-thumbs .card:hover .metadata-button{
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display: inline-block;
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display: inline-block;
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}
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}
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@@ -787,6 +796,13 @@ footer {
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position: relative;
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position: relative;
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}
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}
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.extra-network-thumbs .card .preview{
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position: absolute;
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object-fit: cover;
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width: 100%;
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height:100%;
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}
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.extra-network-thumbs .card:hover .additional a {
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.extra-network-thumbs .card:hover .additional a {
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display: inline-block;
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display: inline-block;
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}
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}
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@@ -291,9 +291,20 @@ def initialize_rest(*, reload_script_modules=False):
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modules.sd_hijack.list_optimizers()
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modules.sd_hijack.list_optimizers()
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startup_timer.record("scripts list_optimizers")
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startup_timer.record("scripts list_optimizers")
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# load model in parallel to other startup stuff
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def load_model():
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# (when reloading, this does nothing)
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"""
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Thread(target=lambda: shared.sd_model).start()
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Accesses shared.sd_model property to load model.
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After it's available, if it has been loaded before this access by some extension,
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its optimization may be None because the list of optimizaers has neet been filled
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by that time, so we apply optimization again.
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"""
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shared.sd_model # noqa: B018
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if modules.sd_hijack.current_optimizer is None:
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modules.sd_hijack.apply_optimizations()
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Thread(target=load_model).start()
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shared.reload_hypernetworks()
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shared.reload_hypernetworks()
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startup_timer.record("reload hypernetworks")
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startup_timer.record("reload hypernetworks")
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Reference in New Issue
Block a user