SD plugin up and running, but with tanked performances...... why

Author: oxysoft

core/cmdargs.py

@@ -8,7 +8,8 @@
 cargs = None
 
 parser = argparse.ArgumentParser()
-parser.add_argument("--dry", type=str, help="Only install and test the core, do not launch server.")
+parser.add_argument("--dry", action='store_true', help="Only install and test the core, do not launch server.")
+parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
 
 # parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN'))
 # parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None)
@@ -23,7 +24,6 @@
 # parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
 # parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram")
 # parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
-# parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
 # parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)")
 # parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
 # parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=modeldir / 'Codeformer')

core/devicelib.py

@@ -26,6 +26,16 @@ def enable_tf32():
         torch.backends.cuda.matmul.allow_tf32 = True
         torch.backends.cudnn.allow_tf32 = True
 
+def set_precision(precision):
+    global dtype
+    global dtype_vae
+
+    if precision == 'full':
+        dtype = torch.float32
+        dtype_vae = torch.float32
+    elif precision == 'autocast':
+        dtype = torch.float16
+        dtype_vae = torch.float16
 
 def randn(seed, shape):
     # Pytorch currently doesn't handle setting randomness correctly when the metal backend is used.
@@ -80,3 +90,5 @@ def autocast(enable=True):
 # device = device
 
 device = get_optimal_device()
+
+print(device)

core/jobs.py

@@ -14,13 +14,16 @@
 class JobParams:
     def __init__(self, **kwargs):
         self.__dict__.update(kwargs)
+        self.job: Job | None = None
 
     @abstractmethod
     def get_plugin_impl(self):
-        pass
+        # TODO it's probably much better to do this in the plugin and then iterate plugins to see which one can handle this jobparams
+        return None, None
 
+    @property
     def plugin(self):
-        return self.job.plugin()
+        return self.job.plugin
 
     def on_start(self, job):
         pass
@@ -46,10 +49,12 @@ def __init__(self, plugin_id: str, plugin_func: str, parameters: JobParams):
         self.image = None
         self.timestamp: str = datetime.now().strftime("%Y%m%d%H%M%S")  # shouldn't this return job_timestamp?
 
+    @property
     def plugin(self):
         import core.plugins
         return core.plugins.get(self.plugin_id)
 
+    @property
     def done(self):
         return self.progress == 1
 
@@ -243,4 +248,4 @@ def is_processing(id):
 
 
 def is_any_processing():
-    return len(queue.processing) > 0
+    return len(queue.processing) > 0

core/plugins.py

@@ -1,11 +1,12 @@
 import importlib
+import os
 import sys
 import traceback
 from pathlib import Path
 
 # Constants
 from core.jobs import JobParams
-from core.printing import printerr
+from core.printing import printerr, print_bp
 
 INIT_NONE = 0
 INIT_ENABLE = 1
@@ -29,9 +30,9 @@ def new_job(self, name, jobparams: JobParams):
         Return a new job
         """
         from core import jobs
-        jobparams.plugin = self
-        return jobs.new_job(self.id, name, jobparams)
-
+        j = jobs.new_job(self.id, name, jobparams)
+        j.plugin_id = self.id
+        return j
     # The title of the script. This is what will be displayed in the dropdown menu.
     def title(self):
         raise NotImplementedError()
@@ -58,6 +59,9 @@ def install(self):
     def uninstall(self):
         pass
 
+    def load(self):
+        pass
+
     # Allows accessing script's attributes by indexing e.g. script['on_run_start']
     def get(self, varname):
         return getattr(self, varname)
@@ -122,15 +126,16 @@ def info(plugid):
 def load(path: Path):
     """
     Manually load a plugin at the given path
+    TODO this function is probably shite
     """
     import inspect
-    from types import ModuleType
 
     # Find classes that extend Plugin in the module
     try:
         sys.path.append(path.as_posix())
         plugin_dirs.append(path)
 
+        # from types import ModuleType
         # # this is missing a bunch of module files for some reason...
         # mod = importlib.import_module(f'modules.{path.stem}')
         #
@@ -142,17 +147,24 @@ def load(path: Path):
         #         plugins.append(plugin)
 
         # TODO probably gonna have to detect by name instead (class & file name must be the same, and end with 'Plugin', e.g. StableDiffusionPlugin)
+
+        if not any(['plugin' in Path(f).name.lower() for f in os.listdir(path)]):
+            return
+
         for f in path.iterdir():
             if f.is_file() and f.suffix == '.py':
                 mod = importlib.import_module(f'modules.{path.stem}.{f.stem}')
                 for name, obj in inspect.getmembers(mod):
-                    if inspect.isclass(obj) and issubclass(obj, Plugin):
+                    if inspect.isclass(obj) and issubclass(obj, Plugin) and not obj == Plugin:
                         # Instantiate the plugin
-                        print(f"Found plugin: {obj}")
+                        # print(f"Loaded plugin: {obj}")
                         plugin = obj(dirpath=path)
                         plugins.append(plugin)
-    except:
-        sys.path.remove(path.as_posix())
+    except Exception as e:
+        printerr(f"Couldn't load plugin {path.name}:")
+        # Print the exception e and its full stacktrace
+        excmsg = ''.join(traceback.format_exception(None, e, e.__traceback__))
+        printerr(excmsg)
         plugin_dirs.remove(path)
 
 
@@ -168,7 +180,9 @@ def load_all(loaddir: Path):
         if p.is_dir() and not p.stem.startswith('__'):
             load(p)
 
-    print(f'Reloaded modules, {len(plugin_dirs)} found')
+    print(f"Loaded {len(plugins)} plugins:")
+    for plugin in plugins:
+        print_bp(f"{plugin.id} ({plugin.dir})")
 
 
 def invoke(plugin, function, default=None, error=False, *args, **kwargs):
@@ -178,12 +192,15 @@ def invoke(plugin, function, default=None, error=False, *args, **kwargs):
     try:
         plug = get(plugin)
         if not plug:
-            if error: printerr(f"Plugin {plugin} not found")
+            if error:
+                printerr(f"Plugin {plugin} not found")
             return default
 
-        attr = getattr(plug, function)
+        attr = getattr(plug, function, None)
         if not attr:
-            if error: printerr(f"Plugin {plugin} has no attribute {function}")
+            if error:
+                printerr(f"Plugin {plugin} has no attribute {function}")
+
             return default
 
         return attr(*args, **kwargs)
@@ -204,6 +221,6 @@ def broadcast(name, *args, **kwargs):
     """
     Dispatch a function call to all plugins.
     """
-    print(f"broadcast({name}, {args}, {kwargs}) to {len(plugins)} plugins")
+    # print(f"broadcast({name}, {args}, {kwargs}) to {len(plugins)} plugins")
     for plugin in plugins:
         invoke(plugin.id, name, None, False, *args, **kwargs)

core/printing.py

@@ -1,6 +1,8 @@
 import sys
 import traceback
 
+def print_bp(msg):
+    print(f' - {msg}')
 
 def printerr(msg):
     import sys

launch.py

@@ -5,12 +5,14 @@
 import sys
 import shlex
 
+import transformers
+
 from core.cmdargs import cargs
 from core.paths import repodir
 from core.installing import is_installed, run, git, git_clone, run_python, run_pip, repo_dir, python
 
 from core.paths import rootdir
-from modules.stable_diffusion.SDJob_txt2img import SDJob_txt2img
+from modules.stable_diffusion_auto1111.SDJob_txt2img import SDJob_txt2img
 
 taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
 torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113")
@@ -63,6 +65,12 @@ def sigint_handler(sig, frame):
 
 
 xformers_available = False
+transformers.logging.set_verbosity_error()
+try:
+    from transformers import logging, CLIPModel
+    logging.set_verbosity_error()
+except Exception:
+    pass
 
 if __name__ == "__main__":
     print_info()
@@ -83,6 +91,10 @@ def sigint_handler(sig, frame):
     sys.argv += args
     cargs = cmdargs.parser.parse_args(args)
 
+    # Prepare core
+    # ----------------------------------------
+    devicelib.set_precision(cargs.precision)
+
     # Prepare plugin system
     # ----------------------------------------
     from core import plugins, options, paths
@@ -104,19 +116,26 @@ def sigint_handler(sig, frame):
 
     # Dry run, only install and exit.
     # ----------------------------------------
+    # plugins.broadcast("load")
+    # plugins.job(SDJob_txt2img(prompt="Beautiful painting of an ultra contorted landscape by Greg Ruktowsky and Salvador Dali. airbrushed, 70s prog rock album cover, psychedelic, elaborate, complex",
+    #                           cfg=7.75,
+    #                           steps=22,
+    #                           sampler='euler-a',
+    #                           ))
+
+    # plugins.get("stable_diffusion_auto1111").txt2img()
+    # plugins.get("stable_diffusion_auto2222").load()
+    plugins.get("stable_diffusion_auto1111").load()
+
+    # plugins.get("stable_diffusion_auto2222").txt2img("Beautiful painting of an ultra contorted landscape by Greg Ruktowsky and Salvador Dali. airbrushed, 70s prog rock album cover, psychedelic, elaborate, complex")
+    plugins.get("stable_diffusion_auto1111").txt2img(SDJob_txt2img(prompt="Beautiful painting of an ultra contorted landscape by Greg Ruktowsky and Salvador Dali. airbrushed, 70s prog rock album cover, psychedelic, elaborate, complex"))
+
     if cargs.dry:
         print("Exiting because of --dry argument")
         exit(0)
 
     # Start server
     # ----------------------------------------
-    plugins.broadcast("launch")  # doubt we need this
-
-    plugins.job(SDJob_txt2img(prompt="Beautiful painting of an ultra contorted landscape by Greg Ruktowsky and Salvador Dali. airbrushed, 70s prog rock album cover, psychedelic, elaborate, complex",
-                              cfg=7.75,
-                              steps=22,
-                              sampler='euler-a',
-                              ))
 
     install_webui()
     start_webui()

modules/params.txt

@@ -0,0 +1 @@
+hehe

modules/repositories/BLIP

@@ -0,0 +1 @@
+Subproject commit 48211a1594f1321b00f14c9f7a5b4813144b2fb9

modules/repositories/CodeFormer

@@ -0,0 +1 @@
+Subproject commit c5b4593074ba6214284d6acd5f1719b6c5d739af

modules/repositories/k-diffusion

@@ -0,0 +1 @@
+Subproject commit f4e99857772fc3a126ba886aadf795a332774878