feat: Shared Diffusion Model Loader (Inspire)

feat: Shared Text Encoder Loader (Inspire)

https://github.com/ltdrdata/ComfyUI-Inspire-Pack/issues/205

README.md

@@ -2,6 +2,7 @@
 This repository offers various extension nodes for ComfyUI. Nodes here have different characteristics compared to those in the ComfyUI Impact Pack. The Impact Pack has become too large now...
 
 ## Notice:
+* v1.9.1 To avoid confusion with the `NOISE` type in core, the type name has been changed to `NOISE_IMAGE`.
 * V0.73 The Variation Seed feature is added to Regional Prompt nodes, and it is only compatible with versions Impact Pack V5.10 and above.
 * V0.69 incompatible with the outdated **ComfyUI IPAdapter Plus**. (A version dated March 24th or later is required.)
 * V0.64 add sigma_factor to RegionalPrompt... nodes required Impact Pack V4.76 or later.
@@ -146,7 +147,11 @@ This repository offers various extension nodes for ComfyUI. Nodes here have diff
   * `Shared Checkpoint Loader (Inspire)`: When loading a checkpoint through this loader, it is automatically cached in the backend cache. Additionally, if it is already cached, it retrieves it from the cache instead of loading it anew.
     * When `key_opt` is empty, the `ckpt_name` is set as the cache key. The cache key output can be used for deletion purposes with Remove Back End.
     * This node resolves the issue of reloading checkpoints during workflow switching.
+  * `Shared Diffusion Model Loader (Inspire)`: Similar to the `Shared Checkpoint Loader (Inspire)` but used for loading Diffusion models instead of Checkpoints.
+  * `Shared Text Encoder Loader (Inspire)`: Similar to the `Shared Checkpoint Loader (Inspire)` but used for loading Text Encoder models instead of Checkpoints.
+    * This node also functions as a unified node for `CLIPLoader`, `DualCLIPLoader`, and `TripleCLIPLoader`. 
   * `Stable Cascade Checkpoint Loader (Inspire)`: This node provides a feature that allows you to load the `stage_b` and `stage_c` checkpoints of Stable Cascade at once, and it also provides a backend caching feature, optionally.
+  * `Is Cached (Inspire)`: Returns whether the cache exists.
 
 ### Conditioning - Nodes for conditionings
   * `Concat Conditionings with Multiplier (Inspire)`: Concatenating an arbitrary number of Conditionings while applying a multiplier for each Conditioning. The multiplier depends on `comfy_PoP`, so [comfy_PoP](https://github.com/picturesonpictures/comfy_PoP) must be installed.

__init__.py

@@ -7,7 +7,7 @@
 
 import importlib
 
-version_code = [1, 8]
+version_code = [1, 10]
 version_str = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 print(f"### Loading: ComfyUI-Inspire-Pack ({version_str})")
 

inspire/a1111_compat.py

@@ -162,7 +162,7 @@ class KSamplerAdvanced_inspire:
                 "optional":
                     {
                         "variation_method": (["linear", "slerp"],),
-                        "noise_opt": ("NOISE",),
+                        "noise_opt": ("NOISE_IMAGE",),
                         "scheduler_func_opt": ("SCHEDULER_FUNC",),
                     }
                 }
@@ -253,7 +253,7 @@ class KSamplerAdvanced_inspire_pipe:
                      },
                 "optional":
                     {
-                        "noise_opt": ("NOISE",),
+                        "noise_opt": ("NOISE_IMAGE",),
                         "scheduler_func_opt": ("SCHEDULER_FUNC",),
                     }
                 }

inspire/backend_support.py

@@ -1,5 +1,6 @@
 import json
 import os
+from .libs import common
 
 import folder_paths
 import nodes
@@ -7,6 +8,8 @@ from server import PromptServer
 
 from .libs.utils import TaggedCache, any_typ
 
+import logging
+
 root_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
 settings_file = os.path.join(root_dir, 'cache_settings.json')
 try:
@@ -400,6 +403,174 @@ class CheckpointLoaderSimpleShared(nodes.CheckpointLoaderSimple):
         return (None, cache_weak_hash(key))
 
 
+class LoadDiffusionModelShared(nodes.UNETLoader):
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "model_name": (folder_paths.get_filename_list("diffusion_models"), {"tooltip": "Diffusion Model Name"}),
+                              "weight_dtype": (["default", "fp8_e4m3fn", "fp8_e4m3fn_fast", "fp8_e5m2"],),
+                              "key_opt": ("STRING", {"multiline": False, "placeholder": "If empty, use 'model_name' as the key."}),
+                              "mode": (['Auto', 'Override Cache', 'Read Only'],),
+                              }
+                }
+    RETURN_TYPES = ("MODEL", "STRING")
+    RETURN_NAMES = ("model", "cache key")
+
+    FUNCTION = "doit"
+
+    CATEGORY = "InspirePack/Backend"
+
+    def doit(self, model_name, weight_dtype, key_opt, mode='Auto'):
+        if mode == 'Read Only':
+            if key_opt.strip() == '':
+                raise Exception("[LoadDiffusionModelShared] key_opt cannot be omit if mode is 'Read Only'")
+            key = key_opt.strip()
+        elif key_opt.strip() == '':
+            key = f"{model_name}_{weight_dtype}"
+        else:
+            key = key_opt.strip()
+
+        if key not in cache or mode == 'Override Cache':
+            model = self.load_unet(model_name, weight_dtype)[0]
+            update_cache(key, "diffusion", (False, model))
+            print(f"[Inspire Pack] LoadDiffusionModelShared: diffusion model '{model_name}' is cached to '{key}'.")
+        else:
+            _, (_, model) = cache[key]
+            print(f"[Inspire Pack] LoadDiffusionModelShared: Cached diffusion model '{key}' is loaded. (Loading skip)")
+
+        return model, key
+
+    @staticmethod
+    def IS_CHANGED(model_name, weight_dtype, key_opt, mode='Auto'):
+        if mode == 'Read Only':
+            if key_opt.strip() == '':
+                raise Exception("[LoadDiffusionModelShared] key_opt cannot be omit if mode is 'Read Only'")
+            key = key_opt.strip()
+        elif key_opt.strip() == '':
+            key = f"{model_name}_{weight_dtype}"
+        else:
+            key = key_opt.strip()
+
+        if mode == 'Read Only':
+            return None, cache_weak_hash(key)
+        elif mode == 'Override Cache':
+            return model_name, key
+
+        return None, cache_weak_hash(key)
+
+
+class LoadTextEncoderShared:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "model_name1": (folder_paths.get_filename_list("text_encoders"), ),
+                              "model_name2": (["None"] + folder_paths.get_filename_list("text_encoders"), ),
+                              "model_name3": (["None"] + folder_paths.get_filename_list("text_encoders"), ),
+                              "type": (["stable_diffusion", "stable_cascade", "sd3", "stable_audio", "mochi", "ltxv", "pixart", "cosmos", "sdxl", "flux", "hunyuan_video"], ),
+                              "key_opt": ("STRING", {"multiline": False, "placeholder": "If empty, use 'model_name' as the key."}),
+                              "mode": (['Auto', 'Override Cache', 'Read Only'],),
+                              },
+                "optional": { "device": (["default", "cpu"], {"advanced": True}), }
+                }
+    RETURN_TYPES = ("CLIP", "STRING")
+    RETURN_NAMES = ("clip", "cache key")
+
+    FUNCTION = "doit"
+
+    CATEGORY = "InspirePack/Backend"
+
+    DESCRIPTION = \
+        ("[Recipes single]\n"
+         "stable_diffusion: clip-l\n"
+         "stable_cascade: clip-g\n"
+         "sd3: t5 / clip-g / clip-l\n"
+         "stable_audio: t5\n"
+         "mochi: t5\n"
+         "cosmos: old t5 xxl\n\n"
+         "[Recipes dual]\n"
+         "sdxl: clip-l, clip-g\n"
+         "sd3: clip-l, clip-g / clip-l, t5 / clip-g, t5\n"
+         "flux: clip-l, t5\n\n"
+         "[Recipes triple]\n"
+         "sd3: clip-l, clip-g, t5")
+
+    def doit(self, model_name1, model_name2, model_name3, type, key_opt, mode='Auto', device="default"):
+        if mode == 'Read Only':
+            if key_opt.strip() == '':
+                raise Exception("[LoadTextEncoderShared] key_opt cannot be omit if mode is 'Read Only'")
+            key = key_opt.strip()
+        elif key_opt.strip() == '':
+            key = model_name1
+            if model_name2 is not None:
+                key += f"_{model_name2}"
+            if model_name3 is not None:
+                key += f"_{model_name3}"
+            key += f"_{type}_{device}"
+        else:
+            key = key_opt.strip()
+
+        if key not in cache or mode == 'Override Cache':
+            if model_name2 != "None" and model_name3 != "None": # triple text encoder
+                if len({model_name1, model_name2, model_name3}) < 3:
+                    logging.error("[LoadTextEncoderShared] The same model has been selected multiple times.")
+                    raise ValueError("The same model has been selected multiple times.")
+
+                if type not in ["sd3"]:
+                    logging.error("[LoadTextEncoderShared] Currently, the triple text encoder is only supported in `sd3`.")
+                    raise ValueError("Currently, the triple text encoder is only supported in `sd3`.")
+
+                res = nodes.NODE_CLASS_MAPPINGS["TripleCLIPLoader"]().load_clip(model_name1, model_name2, model_name3)[0]
+
+            elif model_name2 != "None" or model_name3 != "None": # dual text encoder
+                second_model = model_name2 if model_name2 != "None" else model_name3
+
+                if model_name1 == second_model:
+                    logging.error("[LoadTextEncoderShared] You have selected the same model for both.")
+                    raise ValueError("[LoadTextEncoderShared] You have selected the same model for both.")
+
+                if type not in ["sdxl", "sd3", "flux", "hunyuan_video"]:
+                    logging.error("[LoadTextEncoderShared] Currently, the triple text encoder is only supported in `sdxl, sd3, flux, hunyuan_video`.")
+                    raise ValueError("Currently, the triple text encoder is only supported in `sdxl, sd3, flux, hunyuan_video`.")
+
+                res = nodes.NODE_CLASS_MAPPINGS["DualCLIPLoader"]().load_clip(model_name1, second_model, type=type, device=device)[0]
+
+            else: # single text encoder
+                if type not in ["stable_diffusion", "stable_cascade", "sd3", "stable_audio", "mochi", "ltxv", "pixart", "cosmos"]:
+                    logging.error("[LoadTextEncoderShared] Currently, the single text encoder is only supported in `stable_diffusion, stable_cascade, sd3, stable_audio, mochi, ltxv, pixart, cosmos`.")
+                    raise ValueError("Currently, the single text encoder is only supported in `stable_diffusion, stable_cascade, sd3, stable_audio, mochi, ltxv, pixart, cosmos`.")
+
+                res = nodes.NODE_CLASS_MAPPINGS["CLIPLoader"]().load_clip(model_name1, type=type, device=device)[0]
+
+            update_cache(key, "diffusion", (False, res))
+            print(f"[Inspire Pack] LoadTextEncoderShared: text encoder model set is cached to '{key}'.")
+        else:
+            _, (_, res) = cache[key]
+            print(f"[Inspire Pack] LoadTextEncoderShared: Cached text encoder model set '{key}' is loaded. (Loading skip)")
+
+        return res, key
+
+    @staticmethod
+    def IS_CHANGED(model_name1, model_name2, model_name3, type, key_opt, mode='Auto', device="default"):
+        if mode == 'Read Only':
+            if key_opt.strip() == '':
+                raise Exception("[LoadTextEncoderShared] key_opt cannot be omit if mode is 'Read Only'")
+            key = key_opt.strip()
+        elif key_opt.strip() == '':
+            key = model_name1
+            if model_name2 is not None:
+                key += f"_{model_name2}"
+            if model_name3 is not None:
+                key += f"_{model_name3}"
+            key += f"_{type}_{device}"
+        else:
+            key = key_opt.strip()
+
+        if mode == 'Read Only':
+            return None, cache_weak_hash(key)
+        elif mode == 'Override Cache':
+            return f"{model_name1}_{model_name2}_{model_name3}_{type}_{device}", key
+
+        return None, cache_weak_hash(key)
+
+
 class StableCascade_CheckpointLoader:
     @classmethod
     def INPUT_TYPES(s):
@@ -478,6 +649,74 @@ class StableCascade_CheckpointLoader:
         return b_model, b_vae, c_model, c_vae, clip_vision, clip, key_b, key_c
 
 
+class IsCached:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "key": ("STRING", {"multiline": False}),
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID"
+            }
+        }
+
+    RETURN_TYPES = ("BOOLEAN", )
+    FUNCTION = "doit"
+
+    CATEGORY = "InspirePack/Backend"
+
+    @staticmethod
+    def IS_CHANGED(key, unique_id):
+        return common.is_changed(unique_id, key in cache)
+
+    def doit(self, key, unique_id):
+        return (key in cache,)
+
+
+# WIP: not properly working, yet
+class CacheBridge:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "value": (any_typ,),
+                "mode": ("BOOLEAN", {"default": True, "label_off": "cached", "label_on": "passthrough"}),
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID"
+            }
+        }
+
+    RETURN_TYPES = (any_typ, )
+    RETURN_NAMES = ("value",)
+
+    FUNCTION = "doit"
+
+    CATEGORY = "InspirePack/Backend"
+
+    @staticmethod
+    def IS_CHANGED(value, mode, unique_id):
+        if not mode and unique_id in common.changed_cache:
+            return common.not_changed_value(unique_id)
+        else:
+            return common.changed_value(unique_id)
+
+    def doit(self, value, mode, unique_id):
+        if not mode:
+            # cache mode
+            if unique_id not in common.changed_cache:
+                common.changed_cache[unique_id] = value
+                common.changed_count_cache[unique_id] = 0
+
+            return (common.changed_cache[unique_id],)
+        else:
+            common.changed_cache[unique_id] = value
+            common.changed_count_cache[unique_id] = 0
+
+            return (common.changed_cache[unique_id],)
+
+
 NODE_CLASS_MAPPINGS = {
     "CacheBackendData //Inspire": CacheBackendData,
     "CacheBackendDataNumberKey //Inspire": CacheBackendDataNumberKey,
@@ -489,7 +728,11 @@ NODE_CLASS_MAPPINGS = {
     "RemoveBackendDataNumberKey //Inspire": RemoveBackendDataNumberKey,
     "ShowCachedInfo //Inspire": ShowCachedInfo,
     "CheckpointLoaderSimpleShared //Inspire": CheckpointLoaderSimpleShared,
-    "StableCascade_CheckpointLoader //Inspire": StableCascade_CheckpointLoader
+    "LoadDiffusionModelShared //Inspire": LoadDiffusionModelShared,
+    "LoadTextEncoderShared //Inspire": LoadTextEncoderShared,
+    "StableCascade_CheckpointLoader //Inspire": StableCascade_CheckpointLoader,
+    "IsCached //Inspire": IsCached,
+    # "CacheBridge //Inspire": CacheBridge,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -503,5 +746,9 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "RemoveBackendDataNumberKey //Inspire": "Remove Backend Data [NumberKey] (Inspire)",
     "ShowCachedInfo //Inspire": "Show Cached Info (Inspire)",
     "CheckpointLoaderSimpleShared //Inspire": "Shared Checkpoint Loader (Inspire)",
-    "StableCascade_CheckpointLoader //Inspire": "Stable Cascade Checkpoint Loader (Inspire)"
+    "LoadDiffusionModelShared //Inspire": "Shared Diffusion Model Loader (Inspire)",
+    "LoadTextEncoderShared //Inspire": "Shared Text Encoder Loader (Inspire)",
+    "StableCascade_CheckpointLoader //Inspire": "Stable Cascade Checkpoint Loader (Inspire)",
+    "IsCached //Inspire": "Is Cached (Inspire)",
+    # "CacheBridge //Inspire": "Cache Bridge (Inspire)"
 }

inspire/inspire_server.py

@@ -6,6 +6,7 @@ from enum import Enum
 from . import prompt_support
 from aiohttp import web
 from . import backend_support
+from .libs import common
 
 
 max_seed = 2**32 - 1
@@ -354,6 +355,21 @@ def force_reset_useless_params(json_data):
     return json_data
 
 
+def clear_unused_node_changed_cache(json_data):
+    prompt = json_data['prompt']
+
+    unused = []
+    for x in common.changed_cache.keys():
+        if x not in prompt:
+            unused.append(x)
+
+    for x in unused:
+        del common.changed_cache[x]
+        del common.changed_count_cache[x]
+
+    return json_data
+
+
 def onprompt(json_data):
     prompt_support.list_counter_map = {}
 
@@ -367,6 +383,7 @@ def onprompt(json_data):
     populate_wildcards(json_data)
 
     force_reset_useless_params(json_data)
+    clear_unused_node_changed_cache(json_data)
 
     return json_data
 

inspire/libs/common.py

@@ -12,3 +12,30 @@ def impact_sampling(*args, **kwargs):
         raise Exception(f"[ERROR] You need to install 'ComfyUI-Impact-Pack'")
 
     return nodes.NODE_CLASS_MAPPINGS['RegionalSampler'].separated_sample(*args, **kwargs)
+
+
+changed_count_cache = {}
+changed_cache = {}
+
+
+def changed_value(uid):
+    v = changed_count_cache.get(uid, 0)
+    changed_count_cache[uid] = v + 1
+    return v + 1
+
+
+def not_changed_value(uid):
+    return changed_count_cache.get(uid, 0)
+
+
+def is_changed(uid, value):
+    if uid not in changed_cache or changed_cache[uid] != value:
+        res = changed_value(uid)
+    else:
+        res = not_changed_value(uid)
+
+    changed_cache[uid] = value
+
+    print(f"keys: {changed_cache.keys()}")
+
+    return res

inspire/prompt_support.py

@@ -63,7 +63,8 @@ class LoadPromptsFromDir:
                     }
                 }
 
-    RETURN_TYPES = ("ZIPPED_PROMPT",)
+    RETURN_TYPES = ("ZIPPED_PROMPT", "INT")
+    RETURN_NAMES = ("zipped_prompt", "count")
     OUTPUT_IS_LIST = (True,)
 
     FUNCTION = "doit"
@@ -125,20 +126,21 @@ class LoadPromptsFromDir:
                     prompt_list = re.split(r'\n\s*-+\s*\n', prompt_data)
 
                     for prompt in prompt_list:
-                        pattern = r"positive:(.*?)(?:\n*|$)negative:(.*)"
+                        pattern = r"^(?:(?:positive:(?P<positive>.*?)|negative:(?P<negative>.*?)|name:(?P<name>.*?))\n*)+$"
                         matches = re.search(pattern, prompt, re.DOTALL)
 
                         if matches:
-                            positive_text = matches.group(1).strip()
-                            negative_text = matches.group(2).strip()
-                            result_tuple = (positive_text, negative_text, file_name)
+                            positive_text = matches.group('positive').strip()
+                            negative_text = matches.group('negative').strip()
+                            name_text = matches.group('name').strip() if matches.group('name') else file_name
+                            result_tuple = (positive_text, negative_text, name_text)
                             prompts.append(result_tuple)
                         else:
                             print(f"[WARN] LoadPromptsFromDir: invalid prompt format in '{file_name}'")
             except Exception as e:
                 print(f"[ERROR] LoadPromptsFromDir: an error occurred while processing '{file_name}': {str(e)}\nNOTE: Only files with UTF-8 encoding are supported.")
 
-        return (prompts, )
+        return (prompts, len(prompts),)
 
 
 class LoadPromptsFromFile:
@@ -166,7 +168,8 @@ class LoadPromptsFromFile:
                         }
                 }
 
-    RETURN_TYPES = ("ZIPPED_PROMPT",)
+    RETURN_TYPES = ("ZIPPED_PROMPT", "INT")
+    RETURN_NAMES = ("zipped_prompt", "count")
     OUTPUT_IS_LIST = (True,)
 
     FUNCTION = "doit"
@@ -228,22 +231,23 @@ class LoadPromptsFromFile:
 
             prompt_list = re.split(r'\n\s*-+\s*\n', prompt_data)
 
-            pattern = r"positive:(.*?)(?:\n*|$)negative:(.*)"
+            pattern = r"^(?:(?:positive:(?P<positive>.*?)|negative:(?P<negative>.*?)|name:(?P<name>.*?))\n*)+$"
 
             for p in prompt_list:
                 matches = re.search(pattern, p, re.DOTALL)
 
                 if matches:
-                    positive_text = matches.group(1).strip()
-                    negative_text = matches.group(2).strip()
-                    result_tuple = (positive_text, negative_text, prompt_file)
+                    positive_text = matches.group('positive').strip()
+                    negative_text = matches.group('negative').strip()
+                    name_text = matches.group('name').strip() if matches.group('name') else prompt_file
+                    result_tuple = (positive_text, negative_text, name_text)
                     prompts.append(result_tuple)
                 else:
                     print(f"[WARN] LoadPromptsFromFile: invalid prompt format in '{prompt_file}'")
         except Exception as e:
             print(f"[ERROR] LoadPromptsFromFile: an error occurred while processing '{prompt_file}': {str(e)}\nNOTE: Only files with UTF-8 encoding are supported.")
 
-        return (prompts, )
+        return (prompts, len(prompts),)
 
 
 class LoadSinglePromptFromFile:
@@ -306,13 +310,14 @@ class LoadSinglePromptFromFile:
             except Exception:
                 prompt = prompt_list[-1]
 
-            pattern = r"positive:(.*?)(?:\n*|$)negative:(.*)"
+            pattern = r"^(?:(?:positive:(?P<positive>.*?)|negative:(?P<negative>.*?)|name:(?P<name>.*?))\n*)+$"
             matches = re.search(pattern, prompt, re.DOTALL)
 
             if matches:
-                positive_text = matches.group(1).strip()
-                negative_text = matches.group(2).strip()
-                result_tuple = (positive_text, negative_text, prompt_file)
+                positive_text = matches.group('positive').strip()
+                negative_text = matches.group('negative').strip()
+                name_text = matches.group('name').strip() if matches.group('name') else prompt_file
+                result_tuple = (positive_text, negative_text, name_text)
                 prompts.append(result_tuple)
             else:
                 print(f"[WARN] LoadSinglePromptFromFile: invalid prompt format in '{prompt_file}'")
@@ -682,7 +687,7 @@ class SeedExplorer:
                 }
         }
 
-    RETURN_TYPES = ("NOISE",)
+    RETURN_TYPES = ("NOISE_IMAGE",)
     FUNCTION = "doit"
 
     CATEGORY = "InspirePack/Prompt"
@@ -757,15 +762,15 @@ class CompositeNoise:
     def INPUT_TYPES(s):
         return {
             "required": {
-                "destination": ("NOISE",),
-                "source": ("NOISE",),
+                "destination": ("NOISE_IMAGE",),
+                "source": ("NOISE_IMAGE",),
                 "mode": (["center", "left-top", "right-top", "left-bottom", "right-bottom", "xy"], ),
                 "x": ("INT", {"default": 0, "min": 0, "max": nodes.MAX_RESOLUTION, "step": 8}),
                 "y": ("INT", {"default": 0, "min": 0, "max": nodes.MAX_RESOLUTION, "step": 8}),
             },
         }
 
-    RETURN_TYPES = ("NOISE",)
+    RETURN_TYPES = ("NOISE_IMAGE",)
     FUNCTION = "doit"
 
     CATEGORY = "InspirePack/Prompt"

inspire/regional_nodes.py

@@ -460,7 +460,7 @@ class RegionalSeedExplorerMask:
             "required": {
                 "mask": ("MASK",),
 
-                "noise": ("NOISE",),
+                "noise": ("NOISE_IMAGE",),
                 "seed_prompt": ("STRING", {"multiline": True, "dynamicPrompts": False, "pysssss.autocomplete": False}),
                 "enable_additional": ("BOOLEAN", {"default": True, "label_on": "true", "label_off": "false"}),
                 "additional_seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
@@ -471,7 +471,7 @@ class RegionalSeedExplorerMask:
                 {"variation_method": (["linear", "slerp"],), }
         }
 
-    RETURN_TYPES = ("NOISE",)
+    RETURN_TYPES = ("NOISE_IMAGE",)
     FUNCTION = "doit"
 
     CATEGORY = "InspirePack/Regional"
@@ -517,7 +517,7 @@ class RegionalSeedExplorerColorMask:
                 "color_mask": ("IMAGE",),
                 "mask_color": ("STRING", {"multiline": False, "default": "#FFFFFF"}),
 
-                "noise": ("NOISE",),
+                "noise": ("NOISE_IMAGE",),
                 "seed_prompt": ("STRING", {"multiline": True, "dynamicPrompts": False, "pysssss.autocomplete": False}),
                 "enable_additional": ("BOOLEAN", {"default": True, "label_on": "true", "label_off": "false"}),
                 "additional_seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
@@ -528,7 +528,7 @@ class RegionalSeedExplorerColorMask:
                 {"variation_method": (["linear", "slerp"],), }
         }
 
-    RETURN_TYPES = ("NOISE", "MASK")
+    RETURN_TYPES = ("NOISE_IMAGE", "MASK")
     FUNCTION = "doit"
 
     CATEGORY = "InspirePack/Regional"

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-inspire-pack"
 description = "This extension provides various nodes to support Lora Block Weight, Regional Nodes, Backend Cache, Prompt Utils, List Utils, Noise(Seed) Utils, ... and the Impact Pack."
-version = "1.8"
+version = "1.10"
 license = { file = "LICENSE" }
 dependencies = ["matplotlib", "cachetools"]