Add custom nodes, Civitai loras (LFS), and vast.ai setup script

Includes 30 custom nodes committed directly, 7 Civitai-exclusive
loras stored via Git LFS, and a setup script that installs all
dependencies and downloads HuggingFace-hosted models on vast.ai.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

custom_nodes/comfyui_ultimatesdupscale/test/tensor_utils.py

@@ -0,0 +1,27 @@
+import torchvision.transforms.functional as TF
+
+
+def img_tensor_mae(tensor1, tensor2):
+    """Calculate the mean absolute difference between two image tensors."""
+    # Remove batch dimensions if present
+    tensor1 = tensor1.squeeze(0).cpu()
+    tensor2 = tensor2.squeeze(0).cpu()
+    if tensor1.shape != tensor2.shape:
+        raise ValueError(
+            f"Tensors must have the same shape for comparison. Got {tensor1.shape=} and {tensor2.shape=}."
+        )
+    return (tensor1 - tensor2).abs().mean().item()
+
+
+def blur(tensor, kernel_size=9, sigma=None):
+    """Apply Gaussian blur to an image tensor."""
+    # [1, H, W, C] -> [1, C, H, W]
+    if tensor.ndim == 4:
+        tensor = tensor.permute(0, 3, 1, 2)
+    elif tensor.ndim == 3:
+        tensor = tensor.permute(2, 0, 1).unsqueeze(0)
+    else:
+        raise ValueError(f"Expected a 3D or 4D tensor, got {tensor.ndim=}")
+    return TF.gaussian_blur(tensor, kernel_size=kernel_size, sigma=sigma).permute(  # type: ignore
+        0, 2, 3, 1
+    )