Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -54,6 +54,8 @@ from utils import (
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extract_exif_data,
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create_mask_now,
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download_diffuser_repo,
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progress_step_bar,
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html_template_message,
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escape_html,
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@@ -95,8 +97,8 @@ embed_list = get_model_list(DIRECTORY_EMBEDS)
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embed_list = [
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(os.path.splitext(os.path.basename(emb))[0], emb) for emb in embed_list
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]
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model_list = LOAD_DIFFUSERS_FORMAT_MODEL +
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lora_model_list = get_model_list(DIRECTORY_LORAS)
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lora_model_list.insert(0, "None")
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lora_model_list = lora_model_list + DIFFUSERS_FORMAT_LORAS
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@@ -130,9 +132,28 @@ class GuiSD:
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self.status_loading = False
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self.sleep_loading = 4
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self.last_load = datetime.now()
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def load_new_model(self, model_name, vae_model, task, progress=gr.Progress(track_tqdm=True)):
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vae_model = vae_model if vae_model != "None" else None
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model_type = get_model_type(model_name)
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dtype_model = torch.bfloat16 if model_type == "FLUX" else torch.float16
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@@ -145,6 +166,8 @@ class GuiSD:
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token=True,
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)
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for i in range(68):
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if not self.status_loading:
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self.status_loading = True
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extract_exif_data,
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create_mask_now,
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download_diffuser_repo,
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get_used_storage_gb,
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delete_model,
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progress_step_bar,
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html_template_message,
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escape_html,
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embed_list = [
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(os.path.splitext(os.path.basename(emb))[0], emb) for emb in embed_list
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]
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single_file_model_list = get_model_list(DIRECTORY_MODELS)
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model_list = LOAD_DIFFUSERS_FORMAT_MODEL + single_file_model_list
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lora_model_list = get_model_list(DIRECTORY_LORAS)
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lora_model_list.insert(0, "None")
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lora_model_list = lora_model_list + DIFFUSERS_FORMAT_LORAS
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self.status_loading = False
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self.sleep_loading = 4
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self.last_load = datetime.now()
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self.inventory = []
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def update_storage_models(self, storage_floor_gb=42, required_inventory_for_purge=3):
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while get_used_storage_gb() > storage_floor_gb:
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if len(self.inventory) < required_inventory_for_purge:
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break
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removal_candidate = self.inventory.pop(0)
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delete_model(removal_candidate)
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def update_inventory(self, model_name):
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if model_name not in single_file_model_list:
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self.inventory = [
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m for m in self.inventory if m != model_name
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] + [model_name]
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print(self.inventory)
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def load_new_model(self, model_name, vae_model, task, progress=gr.Progress(track_tqdm=True)):
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self.update_storage_models()
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# download link model > model_name
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vae_model = vae_model if vae_model != "None" else None
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model_type = get_model_type(model_name)
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dtype_model = torch.bfloat16 if model_type == "FLUX" else torch.float16
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token=True,
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)
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self.update_inventory(model_name)
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for i in range(68):
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if not self.status_loading:
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self.status_loading = True
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