commit PurgeVRAM V2 node
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@@ -147,7 +147,7 @@ When this error has occurred, please check the network environment.
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<font size="4">**If the dependency package error after updating, please double clicking ```repair_dependency.bat``` (for Official ComfyUI Protable) or ```repair_dependency_aki.bat``` (for ComfyUI-aki-v1.x) in the plugin folder to reinstall the dependency packages. </font><br />
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* [PurgeVRAM](#PurgeVRAM) node add any output.
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* Commit [PurgeVRAM V2](#PurgeVRAMV2) node.
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* Commit [ChoiceTextPreset](#ChoiceTextPreset) and [TextPreseter](#TextPreseter) nodes, used for preset text and selecting preset text output.
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* [StringCondition](#StringCondition) add the option of comparing strings to determine if they are the same.
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* Commit [NameToColor](#NameToColor) node, Output colors based on their names.
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@@ -1714,6 +1714,10 @@ Node Options:
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* purge_cache: Clean up cache。
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* purge_models: Unload all loaded models。
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### <a id="table1">PurgeVRAMV2</a>
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Unlike PurgeVRM, this node is not mandatory and can access any input in the process while maintaining the original output, allowing for flexible cleaning.
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### <a id="table1">ImageTaggerSave</a>
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+5
-2
@@ -128,7 +128,7 @@ os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
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## 更新说明
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<font size="4">**如果本插件更新后出现依赖包错误,请双击运行插件目录下的```install_requirements.bat```(官方便携包),或 ```install_requirements_aki.bat```(秋叶整合包) 重新安装依赖包。
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* [PurgeVRAM](#PurgeVRAM)增加any输出。
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* 添加 [PurgeVRAM V2](#PurgeVRAMV2) 节点,不强制执行,增加any输出,便于在流程中灵活释放显存。
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* 添加 [ChoiceTextPreset](#ChoiceTextPreset) 和 [TextPreseter](#TextPreseter) 节点,用于预设文本和选择预设文本输出。
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* [StringCondition](#StringCondition) 节点增加比较字符串是否相同功能。
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* 添加 [NameToColor](#NameToColor)节点,根据颜色名称输出颜色。
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@@ -1522,12 +1522,15 @@ BooleanOperator的升级版,增加了节点内数值输入,增加了大于
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### <a id="table1">PurgeVRAM</a>
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清理GPU显存。可以接入任意类型的输入,当执行到这个节点时将清理VRAM以及RAM中的垃圾对象。通常放置在推理任务完成的节点之后,例如VAE Decode节点。
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此节点为强制执行,即接在此节点之前的所有节点都将被执行。
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节点选项说明:
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* purge_cache: 清理缓存。
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* purge_models: 清理已加载的模型。
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### <a id="table1">PurgeVRAMV2</a>
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与PurgeVRAM不同,此节点不是强制执行,可在流程中接入任意输入,并保持原输出,灵活清理。
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### <a id="table1">ImageTaggerSave</a>
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+39
-5
@@ -8,7 +8,39 @@ any = AnyType("*")
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class PurgeVRAM:
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def __init__(self):
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self.NODE_NAME = 'PurgeVRAM'
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"anything": (any, {}),
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"purge_cache": ("BOOLEAN", {"default": True}),
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"purge_models": ("BOOLEAN", {"default": True}),
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},
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"optional": {
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}
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}
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RETURN_TYPES = ()
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FUNCTION = "purge_vram"
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CATEGORY = '😺dzNodes/LayerUtility/SystemIO'
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OUTPUT_NODE = True
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def purge_vram(self, anything, purge_cache, purge_models):
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import torch.cuda
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import gc
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import comfy.model_management
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clear_memory()
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if purge_models:
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comfy.model_management.unload_all_models()
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comfy.model_management.soft_empty_cache()
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return (None,)
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class PurgeVRAM_V2:
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def __init__(self):
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self.NODE_NAME = 'PurgeVRAM V2'
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@classmethod
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def INPUT_TYPES(cls):
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@@ -25,11 +57,11 @@ class PurgeVRAM:
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RETURN_TYPES = (any,)
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RETURN_NAMES = ("any",)
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FUNCTION = "purge_vram"
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FUNCTION = "purge_vram_v2"
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CATEGORY = '😺dzNodes/LayerUtility/SystemIO'
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OUTPUT_NODE = True
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def purge_vram(self, anything, purge_cache, purge_models):
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def purge_vram_v2(self, anything, purge_cache, purge_models):
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clear_memory()
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if purge_models:
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comfy.model_management.unload_all_models()
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@@ -38,9 +70,11 @@ class PurgeVRAM:
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NODE_CLASS_MAPPINGS = {
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"LayerUtility: PurgeVRAM": PurgeVRAM
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"LayerUtility: PurgeVRAM": PurgeVRAM,
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"LayerUtility: PurgeVRAM V2": PurgeVRAM_V2,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"LayerUtility: PurgeVRAM": "LayerUtility: Purge VRAM"
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"LayerUtility: PurgeVRAM": "LayerUtility: Purge VRAM",
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"LayerUtility: PurgeVRAM V2": "LayerUtility: Purge VRAM V2",
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}
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+1
-1
@@ -1,7 +1,7 @@
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[project]
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name = "comfyui_layerstyle"
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description = "A set of nodes for ComfyUI it generate image like Adobe Photoshop's Layer Style. the Drop Shadow is first completed node, and follow-up work is in progress."
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version = "2.0.14"
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version = "2.0.15"
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license = "MIT"
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dependencies = ["numpy", "pillow", "torch", "matplotlib", "Scipy", "scikit_image", "scikit_learn", "opencv-contrib-python", "pymatting", "timm", "colour-science", "transformers", "blend_modes", "huggingface_hub", "loguru"]
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