logs

TNTwise · Dec 15, 2024 · d5c9087 · d5c9087
1 parent b512d2a
commit d5c9087
Showing 1 changed file with 14 additions and 7 deletions.
diff --git a/backend/src/pytorch/InterpolateTorch.py b/backend/src/pytorch/InterpolateTorch.py
@@ -103,6 +103,10 @@ def dynamicScaleCalculation(self,frame1):
     def __call__(self, img1, writeQueue:Queue, transition=False, upscaleModel:UpscalePytorch = None): # type: ignore
         """Perform processing"""
 
+    def initLog(self):
+        printAndLog("Using device: " + str(self.device))
+        printAndLog("Using dtype: " + str(self.dtype))
+
     @torch.inference_mode()
     def norm(self, frame: torch.Tensor):
         return (
@@ -148,25 +152,29 @@ def __init__(
         dtype: str = "auto",
         backend: str = "pytorch",
         UHDMode: bool = False,
+        ensemble: bool = False,
+        dynamicScaledOpticalFlow: bool = False,
         *args,
         **kwargs,
     ):
-
-        printAndLog("Using device: " + str(device))
-
         self.interpolateModel = modelPath
         self.width = width
         self.height = height
         self.device = self.handleDevice(device)
         self.dtype = self.handlePrecision(dtype)
+        if ensemble:
+            print("Ensemble is not implemented for GIMM, disabling", file=sys.stderr)
+        if dynamicScaledOpticalFlow:
+            print("Dynamic Scaled Optical Flow is not implemented for GIMM, disabling",file=sys.stderr)        
+
         self.backend = backend
         self.ceilInterpolateFactor = ceilInterpolateFactor
         self.frame0 = None
         self.scale = 0.5 # GIMM uses fat amounts of vram, needs really low flow resolution for regular resolutions
         if UHDMode:
             self.scale = 0.25 # GIMM uses fat amounts of vram, needs really low flow resolution for UHD
         self.doEncodingOnFrame = False
-
+        self.initLog()
         self._load()
 
     @torch.inference_mode()
@@ -285,8 +293,6 @@ def __init__(
         *args,
         **kwargs,
     ):
-
-
         self.frame0 = None
         self.interpolateModel = modelPath
         self.width = width
@@ -409,13 +415,14 @@ def __init__(
         *args,
         **kwargs,
     ):
-        printAndLog("Using device: " + str(device))
+
         self.interpolateModel = modelPath
         self.width = width
         self.height = height
 
         self.device:torch.device = self.handleDevice(device)
         self.dtype = self.handlePrecision(dtype)
+        self.initLog()
         self.backend = backend
         self.ceilInterpolateFactor = ceilInterpolateFactor
         self.dynamicScaledOpticalFlow = dynamicScaledOpticalFlow