Add comfyui custom node

comfy_latent_interposer.py

@@ -0,0 +1,67 @@
+import torch
+import torch.nn as nn
+from safetensors.torch import load_file
+from huggingface_hub import hf_hub_download
+
+
+class Interposer(nn.Module):
+	"""
+		Basic NN layout, ported from:
+		https://github.com/city96/SD-Latent-Interposer/blob/main/interposer.py
+	"""
+	version = 1.0 # network revision
+	def __init__(self):
+		super().__init__()
+		module_list = [
+			nn.Conv2d(4, 32, kernel_size=5, padding=2),
+			nn.ReLU(),
+			nn.Conv2d(32, 128, kernel_size=7, padding=3),
+			nn.ReLU(),
+			nn.Conv2d(128, 32, kernel_size=7, padding=3),
+			nn.ReLU(),
+			nn.Conv2d(32, 4, kernel_size=5, padding=2),
+		]
+		self.sequential = nn.Sequential(*module_list)
+	def forward(self, x: torch.Tensor) -> torch.Tensor:
+		return self.sequential(x)
+
+
+class LatentInterposer:
+	def __init__(self):
+		pass
+
+	@classmethod
+	def INPUT_TYPES(s):
+		return {
+			"required": {
+				"samples": ("LATENT", ),
+				"latent_src": (["v1", "xl"],),
+				"latent_dst": (["v1", "xl"],),
+			}
+		}
+
+	RETURN_TYPES = ("LATENT",)
+	FUNCTION = "convert"
+	CATEGORY = "latent"
+
+	def convert(self, samples, latent_src, latent_dst):
+		if latent_src == latent_dst:
+			return samples
+		model = Interposer()
+		weights = str(hf_hub_download(
+			repo_id="city96/SD-Latent-Interposer",
+			filename=f"{latent_src}-to-{latent_dst}_interposer-v{model.version}.safetensors")
+		)
+		model.load_state_dict(load_file(weights))
+		lt = samples["samples"]
+		lt = model(lt)
+		del model
+		return ({"samples": lt},)
+
+NODE_CLASS_MAPPINGS = {
+	"LatentInterposer": LatentInterposer,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "LatentInterposer": "Latent Interposer"
+}