redo timers

config.json

@@ -176,7 +176,7 @@
     "sd_hypernetwork_strength": 1.0,
     "sd_hypernetwork": "None",
     "sd_lora": "",
-    "sd_model_checkpoint": "v1-5-pruned-emaonly.safetensors [6ce0161689]",
+    "sd_model_checkpoint": "sd-v15-runwayml.ckpt [cc6cb27103]",
     "sd_vae_as_default": false,
     "sd_vae_checkpoint_cache": 0,
     "sd_vae": "vae-ft-mse-840000-ema-pruned.ckpt",

modules/sd_models.py

@@ -269,14 +269,14 @@ def get_checkpoint_state_dict(checkpoint_info: CheckpointInfo, timer):
         return checkpoints_loaded[checkpoint_info]
 
     res = read_state_dict(checkpoint_info.filename)
-    timer.record("load weights")
+    timer.record("load")
 
     return res
 
 
 def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer):
     sd_model_hash = checkpoint_info.calculate_shorthash()
-    timer.record("calculate hash")
+    timer.record("hash")
 
     shared.opts.data["sd_model_checkpoint"] = checkpoint_info.title
 
@@ -285,7 +285,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
 
     model.load_state_dict(state_dict, strict=False)
     del state_dict
-    timer.record("apply weights")
+    timer.record("apply")
 
     if shared.opts.sd_checkpoint_cache > 0:
         # cache newly loaded model
@@ -293,7 +293,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
 
     if shared.cmd_opts.opt_channelslast:
         model.to(memory_format=torch.channels_last)
-        timer.record("apply channels_last")
+        timer.record("channels")
 
     if not shared.cmd_opts.no_half:
         vae = model.first_stage_model
@@ -333,7 +333,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
     sd_vae.clear_loaded_vae()
     vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename)
     sd_vae.load_vae(model, vae_file, vae_source)
-    timer.record("load vae")
+    timer.record("vae")
 
 
 def enable_midas_autodownload():
@@ -432,12 +432,10 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
 
     clip_is_included_into_sd = sd1_clip_weight in state_dict or sd2_clip_weight in state_dict
 
-    timer.record("find config")
-
     sd_config = OmegaConf.load(checkpoint_config)
     repair_config(sd_config)
 
-    timer.record("load config")
+    timer.record("config")
 
     print(f"Creating model from config: {checkpoint_config}")
 
@@ -450,7 +448,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
 
     sd_model.used_config = checkpoint_config
 
-    timer.record("create model")
+    timer.record("create")
 
     load_model_weights(sd_model, checkpoint_info, state_dict, timer)
 
@@ -459,7 +457,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
     else:
         sd_model.to(shared.device)
 
-    timer.record("device move")
+    timer.record("move")
 
     sd_hijack.model_hijack.hijack(sd_model)
 
@@ -470,13 +468,13 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
 
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True)  # Reload embeddings after model load as they may or may not fit the model
 
-    timer.record("load textual inversion embeddings")
+    timer.record("embeddings")
 
     script_callbacks.model_loaded_callback(sd_model)
 
-    timer.record("scripts callbacks")
+    timer.record("callbacks")
 
-    print(f"Model loaded in {timer.summary()}.")
+    print(f"Model loaded in {timer.summary()}")
 
     return sd_model
 
@@ -527,13 +525,13 @@ def reload_model_weights(sd_model=None, info=None):
         timer.record("hijack")
 
         script_callbacks.model_loaded_callback(sd_model)
-        timer.record("script callbacks")
+        timer.record("callbacks")
 
         if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
             sd_model.to(devices.device)
-            timer.record("device move")
+            timer.record("device")
 
-    print(f"Weights loaded in {timer.summary()}.")
+    print(f"Weights loaded in {timer.summary()}")
 
 def unload_model_weights(sd_model=None, info=None):
     from modules import lowvram, devices, sd_hijack
@@ -551,6 +549,6 @@ def unload_model_weights(sd_model=None, info=None):
         devices.torch_gc()
         torch.cuda.empty_cache()
 
-    print(f"Unloaded weights {timer.summary()}.")
+    print(f"Unloaded weights {timer.summary()}")
 
     return sd_model

modules/timer.py

@@ -24,12 +24,12 @@ class Timer:
     def summary(self):
         res = f"{self.total:.1f}s"
 
-        additions = [x for x in self.records.items() if x[1] >= 0.1]
+        additions = [x for x in self.records.items() if x[1] >= 0.05]
         if not additions:
             return res
 
         res += " ("
-        res += ", ".join([f"{category}: {time_taken:.1f}s" for category, time_taken in additions])
+        res += " ".join([f"{category}={time_taken:.1f}s" for category, time_taken in additions])
         res += ")"
 
         return res

webui.py

@@ -23,7 +23,7 @@ import torchvision
 import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them
 warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
 warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
-startup_timer.record("import torch")
+startup_timer.record("torch")
 
 import gradio
 import ldm.modules.encoders.modules
@@ -58,7 +58,7 @@ from modules import modelloader
 from modules.shared import cmd_opts
 import modules.hypernetworks.hypernetwork
 
-startup_timer.record("import libraries")
+startup_timer.record("libraries")
 
 
 if cmd_opts.server_name:
@@ -79,7 +79,7 @@ def initialize():
         print(f'Torch {getattr(torch, "__long_version__", torch.__version__)} running on CPU')
 
     extensions.list_extensions()
-    startup_timer.record("list extensions")
+    startup_timer.record("extensions")
 
     if cmd_opts.ui_debug_mode:
         shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
@@ -88,28 +88,28 @@ def initialize():
 
     modelloader.cleanup_models()
     modules.sd_models.setup_model()
-    startup_timer.record("list models")
+    startup_timer.record("models")
 
     codeformer.setup_model(cmd_opts.codeformer_models_path)
-    startup_timer.record("setup codeformer")
+    startup_timer.record("codeformer")
 
     gfpgan.setup_model(cmd_opts.gfpgan_models_path)
-    startup_timer.record("setup gfpgan")
+    startup_timer.record("gfpgan")
 
     modelloader.list_builtin_upscalers()
-    startup_timer.record("list builtin upscalers")
+    startup_timer.record("upscalers")
 
     modules.scripts.load_scripts()
-    startup_timer.record("load scripts")
+    startup_timer.record("scripts")
 
     modelloader.load_upscalers()
-    startup_timer.record("load upscalers")
+    startup_timer.record("upscalers")
 
     modules.sd_vae.refresh_vae_list()
-    startup_timer.record("refresh VAE")
+    startup_timer.record("vae")
 
     modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
-    startup_timer.record("refresh textual inversion templates")
+    startup_timer.record("embeddings")
 
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
     shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
@@ -117,7 +117,7 @@ def initialize():
     startup_timer.record("opts onchange")
 
     shared.reload_hypernetworks()
-    startup_timer.record("reload hypernets")
+    startup_timer.record("hypernets")
 
     ui_extra_networks.intialize()
     ui_extra_networks.register_page(ui_extra_networks_textual_inversion.ExtraNetworksPageTextualInversion())
@@ -165,7 +165,7 @@ def load_model():
     shared.opts.data["sd_model_checkpoint"] = shared.sd_model.sd_checkpoint_info.title
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
     shared.state.end()
-    startup_timer.record("load checkpoint")
+    startup_timer.record("checkpoint")
 
 
 def setup_middleware(app):
@@ -196,7 +196,7 @@ def api_only():
 
     modules.script_callbacks.app_started_callback(None, app)
 
-    print(f"Startup time: {startup_timer.summary()}.")
+    print(f"Startup time: {startup_timer.summary()}")
     api.launch(server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", port=cmd_opts.port if cmd_opts.port else 7861)
 
 
@@ -206,13 +206,13 @@ def webui():
 
     if shared.opts.clean_temp_dir_at_start:
         ui_tempdir.cleanup_tmpdr()
-        startup_timer.record("cleanup temp dir")
+        startup_timer.record("cleanup")
 
     modules.script_callbacks.before_ui_callback()
     startup_timer.record("scripts before_ui_callback")
 
     shared.demo = modules.ui.create_ui()
-    startup_timer.record("create ui")
+    startup_timer.record("ui")
 
     if not cmd_opts.no_gradio_queue:
         shared.demo.queue(16)
@@ -247,7 +247,7 @@ def webui():
 
     cmd_opts.autolaunch = False
 
-    startup_timer.record("gradio launch")
+    startup_timer.record("gradio")
 
     app.user_middleware = [x for x in app.user_middleware if x.cls.__name__ != 'CORSMiddleware']
 
@@ -265,7 +265,7 @@ def webui():
 
     load_model()
 
-    print(f"Startup time: {startup_timer.summary()}.")
+    print(f"Startup time: {startup_timer.summary()}")
 
     while True:
         time.sleep(0.1)