Add a LatentRotate node.

nodes.py

@@ -198,6 +198,29 @@ class LatentUpscale:
         s = torch.nn.functional.interpolate(s, size=(height // 8, width // 8), mode=upscale_method)
         return (s,)
 
+class LatentRotate:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "samples": ("LATENT",),
+                              "rotation": (["none", "90 degrees", "180 degrees", "270 degrees"],),
+                              }}
+    RETURN_TYPES = ("LATENT",)
+    FUNCTION = "rotate"
+
+    CATEGORY = "latent"
+
+    def rotate(self, samples, rotation):
+        s = samples.clone()
+        rotate_by = 0
+        if rotation.startswith("90"):
+            rotate_by = 1
+        elif rotation.startswith("180"):
+            rotate_by = 2
+        elif rotation.startswith("270"):
+            rotate_by = 3
+
+        s = torch.rot90(samples, k=rotate_by, dims=[3, 2])
+        return (s,)
 class KSampler:
     def __init__(self, device="cuda"):
         self.device = device
@@ -342,6 +365,7 @@ NODE_CLASS_MAPPINGS = {
     "LoadImage": LoadImage,
     "ConditioningCombine": ConditioningCombine,
     "ConditioningSetArea": ConditioningSetArea,
+    "LatentRotate": LatentRotate,
 }