remove logs and debugs, fix gpu index

src/python/enfugue/api/controller/system.py

@@ -96,7 +96,7 @@ def get_settings(self, request: Request, response: Response) -> Dict[str, Any]:
             inpainting = "never"
 
         settings = {
-            "gpu": self.configuration.get("enfugue.gpu", 0),
+            "gpu": self.configuration.get("enfugue.gpu.index", 0),
             "safe": self.configuration.get("enfugue.safe", True),
             "auth": not (self.configuration.get("enfugue.noauth", True)),
             "max_queued_invocations": self.configuration.get("enfugue.queue", self.manager.DEFAULT_MAX_QUEUED_INVOCATIONS),
@@ -194,7 +194,7 @@ def update_settings(self, request: Request, response: Response) -> None:
             self.user_config["enfugue.downloads.concurrent"] = request.parsed["max_concurrent_downloads"]
 
         if "gpu" in request.parsed:
-            self.user_config["enfugue.gpu"] = int(request.parsed["gpu"])
+            self.user_config["enfugue.gpu.index"] = int(request.parsed["gpu"])
 
         for controlnet in self.CONTROLNETS:
             if controlnet in request.parsed:

src/python/enfugue/diffusion/manager.py

@@ -387,7 +387,7 @@ def device(self) -> torch.device:
         if not hasattr(self, "_device"):
             from enfugue.diffusion.util import get_optimal_device
 
-            self._device = get_optimal_device(self.configuration.get("enfugue.gpu", None))
+            self._device = get_optimal_device(self.configuration.get("enfugue.gpu.index", None))
         return self._device
 
     @device.setter

src/python/enfugue/diffusion/pipeline.py

@@ -2017,7 +2017,6 @@ def predict_noise_residual(
         kwargs: Dict[str, Any] = {}
         if added_cond_kwargs is not None:
             kwargs["added_cond_kwargs"] = added_cond_kwargs
-            self.debug_tensors(**added_cond_kwargs)
         if motion_attention_mask is not None:
             kwargs["motion_attention_mask"] = motion_attention_mask
         return self.unet(
@@ -2306,7 +2305,6 @@ def denoise_unchunked(
             )
             motion_attention_mask = torch.ones_like(motion_attention_audio_mask) * motion_attention_min
             motion_attention_mask += motion_attention_audio_mask * (motion_attention_max - motion_attention_min)
-            logger.critical(motion_attention_mask)
         else:
             motion_attention_mask = None
 

src/python/enfugue/diffusion/util/torch_util/capability_util.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import Tuple, Any, TYPE_CHECKING
+from typing import Tuple, Any, Optional, TYPE_CHECKING
 
 if TYPE_CHECKING:
     from torch import device as Device

src/python/enfugue/interface/server.py

@@ -180,7 +180,7 @@ def prepare_context(self, request: Request, response: Response) -> Dict[str, Any
         ui_config = self.configuration.get("enfugue.ui.app", {})
         if not isinstance(ui_config, dict):
             ui_config = {}
-        logger.critical(self.configuration.get("server.secure", False))
+
         paths = self.configuration["server.cms.path"]
         if not self.configuration.get("server.secure", False) and self.configuration.get("server.domain", None) is None:
             root = f"http://{request.host}/"