107 lines
3.3 KiB
Python
107 lines
3.3 KiB
Python
def size_to_human_readable(size_in_bytes):
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if size_in_bytes < 1024:
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return f"{size_in_bytes} B"
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elif size_in_bytes < 1024**2:
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return f"{size_in_bytes / 1024:.1f} KB"
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elif size_in_bytes < 1024**3:
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return f"{size_in_bytes / 1024**2:.1f} MB"
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elif size_in_bytes < 1024**4:
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return f"{size_in_bytes / 1024**3:.1f} GB"
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else:
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return f"{size_in_bytes / 1024**4:.1f} TB"
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class DebugWatchNode:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"string_field": ("STRING", {
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"multiline": True, #True if you want the field to look like the one on the ClipTextEncode node
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"default": "Connect any of the inputs to get more information."
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}),
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},
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"optional": {
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"model": ("MODEL",),
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"clip": ("CLIP",),
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"vae": ("VAE",),
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"conditioning": ("CONDITIONING",),
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"latent": ("LATENT",),
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},
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}
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RETURN_TYPES = ()
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FUNCTION = "watch"
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OUTPUT_NODE = True
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CATEGORY = "utils"
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def watch(self, string_field, model=None, clip=None, vae=None, CONDITIONING=None, LATENT=None):
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results = ""
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if model:
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results += "MODEL:\n"
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results += "\tArch:\t" + model.model.latent_format.__class__.__name__ + "\n"
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results += f"\tSize:\t{size_to_human_readable(model.size)}\n"
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results += "\n"
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if clip:
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results += "CLIP:\n\n"
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results += str(type(clip.tokenizer)) + "\n"
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results += "\n"
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if vae:
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results += "VAE:\n\n"
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results += str(type(vae.first_stage_model)) + "\n"
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results += "\n"
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return { "ui": { "string_field": results } }
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class DebugWatchModelNode:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"model": ("MODEL",),
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"output": ("STRING", {
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"multiline": True, #True if you want the field to look like the one on the ClipTextEncode node
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"default": "Connect any of the inputs to get more information."
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}),
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},
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}
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RETURN_TYPES = ()
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FUNCTION = "watch"
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OUTPUT_NODE = True
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CATEGORY = "utils"
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def watch(self, output, model=None):
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results = ""
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if model:
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results += "MODEL:\n"
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results += "\tArch:\t" + model.model.latent_format.__class__.__name__ + "\n"
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results += f"\tSize:\t{size_to_human_readable(model.size)}\n"
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results += "\n"
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return { "ui": { "output": results } }
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# Set the web directory, any .js file in that directory will be loaded by the frontend as a frontend extension
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WEB_DIRECTORY = "./js"
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# A dictionary that contains all nodes you want to export with their names
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# NOTE: names should be globally unique
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NODE_CLASS_MAPPINGS = {
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"DebugWatchNode": DebugWatchNode,
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"DebugWatchModelNode": DebugWatchModelNode,
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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NODE_DISPLAY_NAME_MAPPINGS = {
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"DebugWatchNode": "Debug Watch",
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"DebugWatchModelNode": "Debug Watch Model",
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}
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