97 lines
3.4 KiB
Python
97 lines
3.4 KiB
Python
from comfy_api.latest import io
|
|
from .modelLikeCommon import calculate_patches
|
|
from inspect import cleandoc
|
|
from antlr4 import InputStream, CommonTokenStream
|
|
from .Parser.MathExprLexer import MathExprLexer
|
|
from .Parser.MathExprParser import MathExprParser
|
|
import re
|
|
|
|
|
|
class CLIPMathNode(io.ComfyNode):
|
|
"""
|
|
This node enables the use of math expressions on CLIP weights using Autogrow inputs.
|
|
"""
|
|
|
|
@classmethod
|
|
def define_schema(cls) -> io.Schema:
|
|
return io.Schema(
|
|
node_id="mrmth_ag_CLIPMathNode",
|
|
display_name="CLIP Math",
|
|
category="More math",
|
|
inputs=[
|
|
io.Autogrow.Input(id="V",template=io.Autogrow.TemplatePrefix(io.Clip.Input("values"), prefix="V", min=1, max=50)),
|
|
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)),
|
|
io.String.Input(id="Expression", default="I0*(1-F0)+I1*F0", tooltip="Expression to apply on weights"),
|
|
io.Combo.Input(
|
|
id="length_mismatch",
|
|
options=["error", "passthrough", "pad"],
|
|
default="error",
|
|
tooltip="How to handle mismatched layer counts. For models, this usually defaults to broadcast (zero for missing layers)."
|
|
)
|
|
],
|
|
outputs=[
|
|
io.Clip.Output(),
|
|
],
|
|
)
|
|
|
|
tooltip = cleandoc(__doc__)
|
|
|
|
@classmethod
|
|
def check_lazy_status(cls, Expression, V, F, length_mismatch="tile"):
|
|
|
|
input_stream = InputStream(Expression)
|
|
lexer = MathExprLexer(input_stream)
|
|
stream = CommonTokenStream(lexer)
|
|
stream.fill()
|
|
|
|
# Support aliases
|
|
aliases_img = {"a": "V0", "b": "V1", "c": "V2", "d": "V3"}
|
|
aliases_flt = {"w": "F0", "x": "F1", "y": "F2", "z": "F3"}
|
|
|
|
needed = []
|
|
needed1 = []
|
|
for token in filter(lambda t: t.type == MathExprParser.VARIABLE, stream.tokens):
|
|
var_name = token.text
|
|
|
|
if re.match(r"[VF][0-9]+", var_name):
|
|
needed.append(var_name)
|
|
elif var_name in aliases_img:
|
|
needed.append(aliases_img[var_name])
|
|
elif var_name in aliases_flt:
|
|
needed.append(aliases_flt[var_name])
|
|
for v in needed:
|
|
if v.startswith("V"):
|
|
if v not in V or V[v] is None:
|
|
needed1.append(v)
|
|
elif v.startswith("F"):
|
|
if v not in F or F[v] is None:
|
|
needed1.append(v)
|
|
return needed1
|
|
|
|
@classmethod
|
|
def execute(cls, V, F, Expression, length_mismatch="tile") -> io.NodeOutput:
|
|
# Determine reference CLIP
|
|
a = V.get("V0")
|
|
if a is None:
|
|
for m in V.values():
|
|
if m is not None:
|
|
a = m
|
|
break
|
|
if a is None:
|
|
raise ValueError("At least one input CLIP is required.")
|
|
|
|
patcher_a = a.patcher
|
|
|
|
# Prepare CLIP patchers
|
|
patchers_V = {}
|
|
for k, v in V.items():
|
|
if v is not None:
|
|
patchers_V[k] = v.patcher
|
|
|
|
patches = calculate_patches(Expression, patcher_a, None, None, None, 0,0,0,0, V=patchers_V, F=F)
|
|
|
|
out_clip = a.clone()
|
|
if patches:
|
|
out_clip.add_patches(patches, 1.0, 1.0)
|
|
return (out_clip,)
|