108 lines
4.0 KiB
Python
108 lines
4.0 KiB
Python
from inspect import cleandoc
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from comfy_api.latest import io
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import copy
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from antlr4 import InputStream, CommonTokenStream
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from .Parser.MathExprLexer import MathExprLexer
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from .Parser.MathExprParser import MathExprParser
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import re
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from .Stack import MrmthStack
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class VAEMathNode(io.ComfyNode):
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"""
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This node enables the use of math expressions on VAE weights using Autogrow inputs.
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"""
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@classmethod
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def define_schema(cls) -> io.Schema:
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return io.Schema(
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node_id="mrmth_ag_VAEMathNode",
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display_name="VAE Math",
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category="More math",
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inputs=[
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io.Autogrow.Input(id="V",template=io.Autogrow.TemplatePrefix(io.Vae.Input("values"), prefix="V", min=1, max=50)),
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io.Autogrow.Input(id="F", template=io.Autogrow.TemplatePrefix(io.Float.Input("float", default=0.0, optional=True, lazy=True, force_input=True), prefix="F", min=1, max=50)),
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io.String.Input(id="Expression", default="I0*(1-F0)+I1*F0", tooltip="Expression to apply on weights"),
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io.Combo.Input(
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id="length_mismatch",
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options=["tile", "error", "pad"],
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default="error",
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tooltip="How to handle mismatched layer counts. For models, this usually defaults to broadcast (zero for missing layers)."
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),
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MrmthStack.Input(id="stack", tooltip="Access stack between nodes",optional=True)
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],
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outputs=[
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io.Vae.Output(),
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MrmthStack.Output(),
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],
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)
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tooltip = cleandoc(__doc__)
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@classmethod
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def check_lazy_status(cls, Expression, V, F, length_mismatch="tile",stack=dict()):
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input_stream = InputStream(Expression)
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lexer = MathExprLexer(input_stream)
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stream = CommonTokenStream(lexer)
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stream.fill()
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# Support aliases
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aliases_img = {"a": "V0", "b": "V1", "c": "V2", "d": "V3"}
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aliases_flt = {"w": "F0", "x": "F1", "y": "F2", "z": "F3"}
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needed = []
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needed1 = []
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for token in filter(lambda t: t.type == MathExprParser.VARIABLE, stream.tokens):
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var_name = token.text
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if re.match(r"[VF][0-9]+", var_name):
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needed.append(var_name)
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elif var_name in aliases_img:
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needed.append(aliases_img[var_name])
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elif var_name in aliases_flt:
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needed.append(aliases_flt[var_name])
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for v in needed:
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if v.startswith("V"):
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if v not in V or V[v] is None:
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needed1.append(v)
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elif v.startswith("F"):
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if v not in F or F[v] is None:
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needed1.append(v)
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return needed1
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@classmethod
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def execute(cls, V, F, Expression, length_mismatch="tile",stack=dict()) -> io.NodeOutput:
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# Determine reference VAE
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a = V.get("V0")
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if a is None:
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for m in V.values():
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if m is not None:
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a = m
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break
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if a is None:
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raise ValueError("At least one input VAE is required.")
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# Prepare VAE patchers for calculation
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# We need to map VAE wrappers to their patchers for `calculate_patches`
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patchers_V = {}
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for k, v in V.items():
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if v is not None:
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patchers_V[k] = v.patcher
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# Calculate patches using the patchers (weights are in patcher.model.state_dict)
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from .modelLikeCommon import calculate_patches_autogrow
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aliases = {"a": "V0", "b": "V1", "c": "V2", "d": "V3", "w": "F0", "x": "F1", "y": "F2", "z": "F3"}
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patches = calculate_patches_autogrow(Expression, V=patchers_V, F=F, mapping=aliases,stack=stack)
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# VAE does not have a clone method, so we shallow copy and clone the patcher
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out_vae = copy.copy(a)
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out_vae.patcher = a.patcher.clone()
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if patches:
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out_vae.patcher.add_patches(patches, 1.0, 1.0)
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return (out_vae,)
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