Add PatchModelAddDownscale (Kohya Deep Shrink) node.

By adding a downscale to the unet in the first timesteps this node lets
you generate images at higher resolutions with less consistency issues.

comfy_extras/nodes_model_downscale.py

+import torch
+
+class PatchModelAddDownscale:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "model": ("MODEL",),
+                              "block_number": ("INT", {"default": 3, "min": 1, "max": 32, "step": 1}),
+                              "downscale_factor": ("FLOAT", {"default": 2.0, "min": 0.1, "max": 9.0, "step": 0.001}),
+                              "start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
+                              "end_percent": ("FLOAT", {"default": 0.35, "min": 0.0, "max": 1.0, "step": 0.001}),
+                              }}
+    RETURN_TYPES = ("MODEL",)
+    FUNCTION = "patch"
+
+    CATEGORY = "_for_testing"
+
+    def patch(self, model, block_number, downscale_factor, start_percent, end_percent):
+        sigma_start = model.model.model_sampling.percent_to_sigma(start_percent).item()
+        sigma_end = model.model.model_sampling.percent_to_sigma(end_percent).item()
+
+        def input_block_patch(h, transformer_options):
+            if transformer_options["block"][1] == block_number:
+                sigma = transformer_options["sigmas"][0].item()
+                if sigma <= sigma_start and sigma >= sigma_end:
+                    h = torch.nn.functional.interpolate(h, scale_factor=(1.0 / downscale_factor), mode="bicubic", align_corners=False)
+            return h
+
+        def output_block_patch(h, hsp, transformer_options):
+            if h.shape[2] != hsp.shape[2]:
+                h = torch.nn.functional.interpolate(h, size=(hsp.shape[2], hsp.shape[3]), mode="bicubic", align_corners=False)
+            return h, hsp
+
+        m = model.clone()
+        m.set_model_input_block_patch(input_block_patch)
+        m.set_model_output_block_patch(output_block_patch)
+        return (m, )
+
+NODE_CLASS_MAPPINGS = {
+    "PatchModelAddDownscale": PatchModelAddDownscale,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    # Sampling
+    "PatchModelAddDownscale": "PatchModelAddDownscale (Kohya Deep Shrink)",
+}

nodes.py

@@ -1799,6 +1799,7 @@ def init_custom_nodes():
         "nodes_custom_sampler.py",
         "nodes_hypertile.py",
         "nodes_model_advanced.py",
+        "nodes_model_downscale.py",
     ]
 
     for node_file in extras_files: