diff --git a/base.py b/base.py
index f4d4c77..1c90f1e 100644
--- a/base.py
+++ b/base.py
@@ -44,3 +44,111 @@ class SeedContext():
             random.seed(self.seed)
     def __exit__(self, exc_type, exc_val, exc_tb):
         random.setstate(self.state)
+
+
+# import comfy.model_base as BaseModel
+
+
+class xy_Tiling_KSampler:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": ("MODEL",),
+
+                "seed": ("SEED", ),
+                "steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
+                "cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
+                "sampler_name": (comfy.samplers.KSampler.SAMPLERS, ),
+                "scheduler": (comfy.samplers.KSampler.SCHEDULERS, ),
+                "positive": ("CONDITIONING", ),
+                "negative": ("CONDITIONING", ),
+                "latent_image": ("LATENT", ),
+                "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
+
+                # here is custom config
+                "step_range": ("INT", {
+                    "startStep": 0,  # Start tiling from step N
+                    "stopStep": -1  # Stop tiling after step N (-1: Don't stop)
+                }),
+                "tileX": (["enable", "disable"],),
+                "tileY": (["enable", "disable"],)
+            },
+        }
+
+    RETURN_TYPES = ("LATENT",)
+
+    FUNCTION = "sample"
+
+    CATEGORY = "Alsritter/Sampling"
+
+    def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
+               step_range, tileX, tileY, denoise=1.0):
+
+        if tileX != "enable" and tileY != "enable":
+            return nodes.common_ksampler(model, seed['seed'], steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
+        else:
+            return self.tile_ksampler(model, seed['seed'], steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
+
+    # Self-determined 
+    def tile_ksampler(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False):
+
+        # ========================== Base code ==========================
+        device = comfy.model_management.get_torch_device()
+        latent_image = latent["samples"]
+
+        if disable_noise:
+            noise = torch.zeros(latent_image.size(
+            ), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
+        else:
+            batch_inds = latent["batch_index"] if "batch_index" in latent else None
+            noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)
+
+        noise_mask = None
+        if "noise_mask" in latent:
+            noise_mask = latent["noise_mask"]
+
+        preview_format = "JPEG"
+        if preview_format not in ["JPEG", "PNG"]:
+            preview_format = "JPEG"
+
+        previewer = latent_preview.get_previewer(
+            device, model.model.latent_format)
+
+        # Arrangement progress clause
+        pbar = comfy.utils.ProgressBar(steps)
+
+        def callback(step, x0, x, total_steps):
+            preview_bytes = None
+
+            self.print_object_info(step)
+            self.print_object_info(x0)
+            self.print_object_info(x)
+            self.print_object_info(total_steps)
+
+            #Generation guide
+            if previewer:
+                preview_bytes = previewer.decode_latent_to_preview_image(
+                    preview_format, x0)
+            # Update progress clause
+            pbar.update_absolute(step + 1, total_steps, preview_bytes)
+
+      # ========================== Custom code ==========================
+
+        samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
+                                      denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step,
+                                      force_full_denoise=force_full_denoise, noise_mask=noise_mask, callback=callback, seed=seed)
+        out = latent.copy()
+        out["samples"] = samples
+        return (out, )
+
+    def print_object_info(self, obj):
+        print("Type:", type(obj))
+        print("Attributes and methods:", end=" ")
+        for item in dir(obj):
+            print(item, end=" ")
+
+