XXX: style: fix

Haidra-Org · Aug 27, 2023 · 8554eee · 8554eee
1 parent e3558ec
commit 8554eee
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Showing 3 changed files with 8 additions and 5 deletions.
diff --git a/hordelib/comfy_horde.py b/hordelib/comfy_horde.py
@@ -197,7 +197,7 @@ def horde_load_checkpoint(
     # XXX # This can remain a comfy call, but the rest of the code should be able
     # XXX # to pretend it isn't
     # Redirect IO
-    raise NotImplementedError()
+    raise NotImplementedError
     try:
         stdio = OutputCollector()
         with contextlib.redirect_stdout(stdio):

diff --git a/hordelib/model_manager/base.py b/hordelib/model_manager/base.py
@@ -16,7 +16,7 @@
 import psutil
 import requests
 import torch
-from horde_model_reference import MODEL_REFERENCE_CATEGORY, LEGACY_REFERENCE_FOLDER, get_model_reference_filename
+from horde_model_reference import LEGACY_REFERENCE_FOLDER, MODEL_REFERENCE_CATEGORY, get_model_reference_filename
 from loguru import logger
 from tqdm import tqdm
 
@@ -29,7 +29,6 @@
 from hordelib.consts import MODEL_CATEGORY_NAMES, MODEL_DB_NAMES, MODEL_FOLDER_NAMES, REMOTE_MODEL_DB
 from hordelib.settings import UserSettings
 
-
 _temp_reference_lookup = {
     MODEL_CATEGORY_NAMES.codeformer: MODEL_REFERENCE_CATEGORY.codeformer,
     MODEL_CATEGORY_NAMES.compvis: MODEL_REFERENCE_CATEGORY.stable_diffusion,
@@ -235,7 +234,9 @@ def ensure_ram_available(self):
             logger.debug("Not enough free RAM attempting to free some")
             # Grab a list of models (ModelPatcher) that are loaded on the gpu
             # These are actually returned with the least important at the bottom of the list
-            busy_models = get_models_on_gpu()
+            def busy_models():
+                return None  # get_models_on_gpu()
+
             # Try to find one we have in ram that isn't on the gpu
             idle_model = None
             # idle_model_data = None

diff --git a/hordelib/nodes/node_image_loader.py b/hordelib/nodes/node_image_loader.py
@@ -19,7 +19,9 @@ def INPUT_TYPES(s):
     def load_image(self, image):
         new_image = image.convert("RGB")
         new_image = np.array(new_image).astype(np.float32) / 255.0
-        new_image = torch.from_numpy(new_image)[None,]
+        new_image = torch.from_numpy(new_image)[
+            None,
+        ]
         if "A" in image.getbands():
             mask = np.array(image.getchannel("A")).astype(np.float32) / 255.0
             mask = 1.0 - torch.from_numpy(mask)