add glora

CHANGELOG.md

@@ -62,7 +62,8 @@
       can remove artifacts and hard edges of inpaint area but also remove some details from original  
     - **chaiNNer** fix `NaN` issues due to autocast  
     - **Upscale** increase limit from 4x to 8x given the quality of some upscalers  
-    - **Extra Networks** fix sort
+    - **Extra Networks** fix sort  
+    - **LoRA** add support for LyCORIS GLora networks
     - disable google fonts check on server startup  
     - fix torchvision/basicsr compatibility  
     - fix styles quick save  

extensions-builtin/Lora/network_glora.py

@@ -0,0 +1,30 @@
+
+import network
+
+class ModuleTypeGLora(network.ModuleType):
+    def create_module(self, net: network.Network, weights: network.NetworkWeights):
+        if all(x in weights.w for x in ["a1.weight", "a2.weight", "alpha", "b1.weight", "b2.weight"]):
+            return NetworkModuleGLora(net, weights)
+        return None
+
+# adapted from https://github.com/KohakuBlueleaf/LyCORIS
+class NetworkModuleGLora(network.NetworkModule): # pylint: disable=abstract-method
+    def __init__(self,  net: network.Network, weights: network.NetworkWeights):
+        super().__init__(net, weights)
+
+        if hasattr(self.sd_module, 'weight'):
+            self.shape = self.sd_module.weight.shape
+
+        self.w1a = weights.w["a1.weight"]
+        self.w1b = weights.w["b1.weight"]
+        self.w2a = weights.w["a2.weight"]
+        self.w2b = weights.w["b2.weight"]
+
+    def calc_updown(self, orig_weight): # pylint: disable=arguments-differ
+        w1a = self.w1a.to(orig_weight.device, dtype=orig_weight.dtype)
+        w1b = self.w1b.to(orig_weight.device, dtype=orig_weight.dtype)
+        w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype)
+        w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype)
+        output_shape = [w1a.size(0), w1b.size(1)]
+        updown = (w2b @ w1b) + ((orig_weight @ w2a) @ w1a)
+        return self.finalize_updown(updown, orig_weight, output_shape)

extensions-builtin/Lora/networks.py

@@ -11,6 +11,7 @@ import network_oft
 import network_lokr
 import network_full
 import network_norm
+import network_glora
 import lora_convert
 import torch
 import diffusers.models.lora
@@ -37,6 +38,7 @@ module_types = [
     network_lokr.ModuleTypeLokr(),
     network_full.ModuleTypeFull(),
     network_norm.ModuleTypeNorm(),
+    network_glora.ModuleTypeGLora(),
 ]
 convert_diffusers_name_to_compvis = lora_convert.convert_diffusers_name_to_compvis # supermerger compatibility item
 

html/locale_en.json

@@ -500,7 +500,7 @@
   {"id":"","label":"Show previews of all images generated in a batch as a grid","localized":"","hint":""},
   {"id":"","label":"Play a sound when images are finished generating","localized":"","hint":""},
   {"id":"","label":"Path to notification sound","localized":"","hint":""},
-  {"id":"","label":"Live preview display period","localized":"","hint":""},
+  {"id":"","label":"Live preview display period","localized":"","hint":"Request preview image every n steps, set to 0 to disable"},
   {"id":"","label":"Full VAE","localized":"","hint":""},
   {"id":"","label":"Approximate","localized":"","hint":"Cheap neural network approximation. Very fast compared to VAE, but produces pictures with 4 times smaller horizontal/vertical resolution and lower quality"},
   {"id":"","label":"Simple","localized":"","hint":"Very cheap approximation. Very fast compared to VAE, but produces pictures with 8 times smaller horizontal/vertical resolution and extremely low quality"},

modules/processing_diffusers.py

@@ -651,6 +651,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
             )
             shared.state.sampling_steps = refiner_args['num_inference_steps']
             try:
+                shared.sd_refiner.register_to_config(requires_aesthetics_score=shared.opts.diffusers_aesthetics_score)
+                print('HERE req', shared.sd_refiner.config.requires_aesthetics_score)
                 refiner_output = shared.sd_refiner(**refiner_args) # pylint: disable=not-callable
             except AssertionError as e:
                 shared.log.info(e)

modules/shared.py

@@ -496,7 +496,7 @@ options_templates.update(options_section(('live-preview', "Live Previews"), {
     "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid", gr.Checkbox, {"visible": False}),
     "notification_audio_enable": OptionInfo(False, "Play a sound when images are finished generating"),
     "notification_audio_path": OptionInfo("html/notification.mp3","Path to notification sound", component_args=hide_dirs, folder=True),
-    "show_progress_every_n_steps": OptionInfo(1, "Live preview display period", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
+    "show_progress_every_n_steps": OptionInfo(1, "Live preview display period", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),
     "show_progress_type": OptionInfo("Approximate", "Live preview method", gr.Radio, {"choices": ["Simple", "Approximate", "TAESD", "Full VAE"]}),
     "live_preview_content": OptionInfo("Combined", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"], "visible": False}),
     "live_preview_refresh_period": OptionInfo(500, "Progress update period", gr.Slider, {"minimum": 0, "maximum": 5000, "step": 25}),

modules/ui.py

@@ -366,7 +366,7 @@ def create_toprow(is_img2img: bool = False, id_part: str = None):
                 negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")
             with gr.Row(elem_id=f"{id_part}_styles_row"):
                 styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[style.name for style in modules.shared.prompt_styles.styles.values()], value=[], multiselect=True)
-                styles_btn_refresh = create_refresh_button(styles, modules.shared.prompt_styles.reload, lambda: {"choices": list(modules.shared.prompt_styles.styles)}, f"{id_part}_styles_refresh")
+                _styles_btn_refresh = create_refresh_button(styles, modules.shared.prompt_styles.reload, lambda: {"choices": list(modules.shared.prompt_styles.styles)}, f"{id_part}_styles_refresh")
                 # styles_btn_refresh = ToolButton(symbols.refresh, elem_id=f"{id_part}_styles_refresh", visible=True)
                 # styles_btn_refresh.click(fn=lambda: gr.update(choices=[style.name for style in modules.shared.prompt_styles.styles.values()]), inputs=[], outputs=[styles])
                 styles_btn_select = gr.Button('Select', elem_id=f"{id_part}_styles_select", visible=False)