Merge pull request #2 from dmarx/dev

"Scheduling" nodes with support for AnimateDiff
2023-12-08 08:37:23 -08:00
parent a6fb8b6213 6372ce8fcb
commit a4b47f4ce5
6 changed files with 882 additions and 10 deletions
@@ -29,11 +29,4 @@ from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS

 print(os.environ.get('COMFYUI_DEBUG_MODE'))

-from .debug import NODE_CLASS_MAPPINGS as ncm0, NODE_DISPLAY_NAME_MAPPINGS as ndnm0
-
-# there's probably a cleaner, more-dummy-proof way to do this.
-# feels like an accident waiting to happen. low risk though.
-NODE_CLASS_MAPPINGS.update(ncm0)
-NODE_DISPLAY_NAME_MAPPINGS.update(ndnm0)
-
 __all__ =["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
@@ -0,0 +1,18 @@
+
+from .core import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+from .debug import NODE_CLASS_MAPPINGS as ncm0, NODE_DISPLAY_NAME_MAPPINGS as ndnm0
+from .entangled import NODE_CLASS_MAPPINGS as ncm1, NODE_DISPLAY_NAME_MAPPINGS as ndnm1
+from .schedule import NODE_CLASS_MAPPINGS as ncm2, NODE_DISPLAY_NAME_MAPPINGS as ndnm2
+
+
+# there's probably a cleaner, more-dummy-proof way to do this.
+# feels like an accident waiting to happen. low risk though.
+NODE_CLASS_MAPPINGS.update(ncm0)
+NODE_CLASS_MAPPINGS.update(ncm1)
+NODE_CLASS_MAPPINGS.update(ncm2)
+NODE_DISPLAY_NAME_MAPPINGS.update(ndnm0)
+NODE_DISPLAY_NAME_MAPPINGS.update(ndnm1)
+NODE_DISPLAY_NAME_MAPPINGS.update(ndnm2)
+
+
+__all__ =["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
@@ -69,7 +69,7 @@ label: foo"""


 class KfEvaluateCurveAtT:
-    CATEGORY=CATEGORY
+    CATEGORY=CATEGORY # TODO: create a "utils" group
    FUNCTION = 'main'
    RETURN_TYPES = ("FLOAT","INT")

@@ -313,6 +313,8 @@ class KfCurvesMultiply:
        return (curve_1 * curve_2, )


+## This seems to not be working properly. I think the issue is upstream in Keyframed
+# TODO: set as experimental?
 class KfCurvesDivide:
    CATEGORY = CATEGORY
    FUNCTION = "main"
@@ -331,9 +333,26 @@ class KfCurvesDivide:
        return (curve_1 / curve_2, )


+class KfCurveConstant:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "value": ("FLOAT", {"forceInput": True,})
+                }}
+    
+    def main(self, value):
+        curve = kf.Curve(value)
+        return (curve,)
+
+
 ##################################################################

-#### Working with parameter groups
+### TODO: Working with parameter groups


 # Label curve
@@ -351,6 +370,257 @@ class KfCurvesDivide:
 # extract a time slice from the parameter group


+##################################################################
+
+### Sinusoidal
+
+class KfSinusoidalWithFrequency:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "frequency": ("FLOAT",{
+                    "default": 1/12,
+                    "step": 0.01,
+                }),
+                "phase": ("FLOAT", {
+                    "default": 0.0,
+                    #"min": 0.0,
+                    #"max": 6.28318530718, # 2*pi
+                    "step": 0.1308996939, # pi/24
+                }),
+                "amplitude": ("FLOAT",{
+                    "default": 1,
+                    "step": 0.01,
+                }),
+            },
+        }
+
+    def main(self, frequency, phase, amplitude):
+        curve = kf.SinusoidalCurve(frequency=frequency, phase=phase, amplitude=amplitude)
+        return (curve, curve)
+
+class KfSinusoidalWithWavelength:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "wavelength": ("FLOAT",{
+                    "default": 12,
+                    "step": 0.5,
+                }),
+                "phase": ("FLOAT", {
+                    "default": 0.0,
+                    #"min": 0.0,
+                    #"max": 6.28318530718, # 2*pi
+                    "step": 0.1308996939, # pi/24
+                }),
+                "amplitude": ("FLOAT",{
+                    "default": 1,
+                    "step": 0.01,
+                }),
+            },
+        }
+
+    def main(self, wavelength, phase, amplitude):
+        curve = kf.SinusoidalCurve(wavelength=wavelength, phase=phase, amplitude=amplitude)
+        return (curve, curve)
+
+
+###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #
+
+
+###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #
+
+class KfSinusoidalAdjustWavelength:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+                "adjustment": ("FLOAT",{
+                    "default": 0.0,
+                    "step": 0.5,
+                }),
+            }}
+
+    def main(self, curve, adjustment):
+        wavelength, phase, amplitude = curve.wavelength, curve.phase, curve.amplitude 
+        wavelength += adjustment
+        curve = kf.SinusoidalCurve(wavelength=wavelength, phase=phase, amplitude=amplitude)
+        return (curve, curve)
+
+
+class KfSinusoidalAdjustPhase:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+                "adjustment": ("FLOAT", {
+                    "default": 0.0,
+                    "step": 0.1308996939, # pi/24
+                }),
+            }}
+    
+    def main(self, curve, adjustment):
+        wavelength, phase, amplitude = curve.wavelength, curve.phase, curve.amplitude 
+        phase += adjustment
+        curve = kf.SinusoidalCurve(wavelength=wavelength, phase=phase, amplitude=amplitude)
+        return (curve, curve)
+
+
+class KfSinusoidalAdjustFrequency:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+                "adjustment": ("FLOAT",{
+                    "default": 0,
+                    "step": 0.01,
+                }),
+            }}
+
+    def main(self, curve, adjustment):
+        wavelength, phase, amplitude = curve.wavelength, curve.phase, curve.amplitude
+        frequency = 1/wavelength
+        frequency += adjustment
+        wavelength = 1/frequency
+        curve = kf.SinusoidalCurve(wavelength=wavelength, phase=phase, amplitude=amplitude)
+        return (curve, curve)
+    
+
+class KfSinusoidalAdjustAmplitude:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+                "adjustment": ("FLOAT",{
+                    "default": 0,
+                    "step": 0.01,
+                }),
+            }}
+
+    def main(self, curve, adjustment):
+        wavelength, phase, amplitude = curve.wavelength, curve.phase, curve.amplitude 
+        amplitude += adjustment
+        curve = kf.SinusoidalCurve(wavelength=wavelength, phase=phase, amplitude=amplitude)
+        return (curve, curve)
+
+
+###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #   ###   #
+
+
+class KfSinusoidalGetWavelength:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("FLOAT",)
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+            }}
+
+    def main(self, curve):
+        return (curve.wavelength,)
+
+
+class KfSinusoidalGetFrequency:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("FLOAT",)
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+            }}
+
+    def main(self, curve):
+        return (1/curve.wavelength,)
+
+
+class KfSinusoidalGetPhase:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("FLOAT",)
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+            }}
+
+    def main(self, curve):
+        return (curve.phase,)
+
+
+class KfSinusoidalGetAmplitude:
+    CATEGORY = CATEGORY
+    FUNCTION = "main"
+    RETURN_TYPES = ("FLOAT",)
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "curve": ("SINUSOIDAL_CURVE",{"forceInput": True,}),
+            }}
+
+    def main(self, curve):
+        return (curve.amplitude,)
+
+##################################################################
+
+
+# KfScheduleConditions:
+#     """
+#     Carry curve and cond together for Simplicity
+#     """
+#     CATEGORY = CATEGORY
+#     FUNCTION = "main"
+#     RETURN_TYPES = ("COND_SCHEDULE",)
+
+
+# KfCombineWeightedConditions:
+
+##################################################################
+
+# TODO: 0-1 curves (low frequency oscillators)
+# --> "1-X" operator
+
+# TODO: pre-entangled curves
+
 ##################################################################

 NODE_CLASS_MAPPINGS = {
@@ -359,13 +629,26 @@ NODE_CLASS_MAPPINGS = {
    "KfEvaluateCurveAtT": KfEvaluateCurveAtT,
    "KfApplyCurveToCond": KfApplyCurveToCond,
    "KfConditioningAdd": KfConditioningAdd,
+    #"KfCurveToAcnLatentKeyframe": KfCurveToAcnLatentKeyframe,
+    #######################################
    #"KfCurveInverse": KfCurveInverse,
    "KfCurveDraw": KfCurveDraw,
    "KfCurvesAdd": KfCurvesAdd,
    "KfCurvesSubtract": KfCurvesSubtract,
    "KfCurvesMultiply": KfCurvesMultiply,
    "KfCurvesDivide": KfCurvesDivide,
-    #"KfCurveToAcnLatentKeyframe": KfCurveToAcnLatentKeyframe,
+    "KfCurveConstant": KfCurveConstant,
+    #########################
+    "KfSinusoidalWithFrequency": KfSinusoidalWithFrequency,
+    "KfSinusoidalWithWavelength": KfSinusoidalWithWavelength,
+    "KfSinusoidalAdjustWavelength": KfSinusoidalAdjustWavelength,
+    "KfSinusoidalAdjustPhase": KfSinusoidalAdjustPhase,
+    "KfSinusoidalAdjustFrequency": KfSinusoidalAdjustFrequency,
+    "KfSinusoidalAdjustAmplitude": KfSinusoidalAdjustAmplitude,
+    "KfSinusoidalGetWavelength": KfSinusoidalGetWavelength,
+    "KfSinusoidalGetPhase": KfSinusoidalGetPhase,
+    "KfSinusoidalGetAmplitude": KfSinusoidalGetAmplitude,
+    "KfSinusoidalGetFrequency": KfSinusoidalGetFrequency,
 }

 # A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -0,0 +1,172 @@
+from .core import CATEGORY
+import keyframed as kf
+import numpy as np
+
+class KfSinusoidalEntangledZeroOne:
+    CATEGORY = CATEGORY + "/entangled [0-1]"
+    FUNCTION = "main"
+    #RETURN_TYPES = ("KEYFRAMED_CURVE", "SINUSOIDAL_CURVE")
+
+    def main(self, n, **kargs):
+        tau = 2*np.pi 
+        floor=.001 # fully zeroing out conditions creates "sharp edges" in the traversal
+        a = 1/n
+        amplitude = a - floor/2
+
+        
+        #return [a+kf.SinusoidalCurve(phase=i/tau, amplitude=a, **kargs) for i in range(n)]
+        return [amplitude+kf.SinusoidalCurve(phase=tau*(n-i-1)/n, amplitude=amplitude, **kargs) for i in range(n)]
+
+
+class KfSinusoidalEntangledZeroOneFromWavelength(KfSinusoidalEntangledZeroOne):
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "wavelength": ("FLOAT",{
+                    "default": 12,
+                    "step": 0.5,
+                }),
+            }
+        }
+    
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx2(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*2
+    def main(self, wavelength):
+        return super().main(n=2, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx3(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*3
+    def main(self, wavelength):
+        return super().main(n=3, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx4(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*4
+    def main(self, wavelength):
+        return super().main(n=4, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx5(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*5
+    def main(self, wavelength):
+        return super().main(n=5, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx6(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*6
+    def main(self, wavelength):
+        return super().main(n=6, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx7(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*7
+    def main(self, wavelength):
+        return super().main(n=7, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx8(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*8
+    def main(self, wavelength):
+        return super().main(n=8, wavelength=wavelength)
+
+class KfSinusoidalEntangledZeroOneFromWavelengthx9(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*9
+    def main(self, wavelength):
+        return super().main(n=9, wavelength=wavelength)
+
+
+###############################################################################################
+
+class KfSinusoidalEntangledZeroOneFromFrequency(KfSinusoidalEntangledZeroOne):
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                 "frequency": ("FLOAT",{
+                    "default": 1/12,
+                    "step": 0.01,
+                }),
+            }
+        }
+
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx2(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*2
+    def main(self, frequency):
+        return super().main(n=2, frequency=frequency)
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx3(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*3
+    def main(self, frequency):
+        return super().main(n=3, frequency=frequency)
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx4(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*4
+    def main(self, frequency):
+        return super().main(n=4, frequency=frequency)
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx5(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*5
+    def main(self, frequency):
+        return super().main(n=5, frequency=frequency)
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx6(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*6
+    def main(self, frequency):
+        return super().main(n=6, frequency=frequency)
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx7(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*7
+    def main(self, frequency):
+        return super().main(n=7, frequency=frequency)
+    
+class KfSinusoidalEntangledZeroOneFromFrequencyx8(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*8
+    def main(self, frequency):
+        return super().main(n=8, frequency=frequency)
+
+class KfSinusoidalEntangledZeroOneFromFrequencyx9(KfSinusoidalEntangledZeroOneFromWavelength):
+    RETURN_TYPES = ("KEYFRAMED_CURVE",)*9
+    def main(self, frequency):
+        return super().main(n=9, frequency=frequency)
+
+
+###############################################################################################
+
+NODE_CLASS_MAPPINGS = {
+    "KfSinusoidalEntangledZeroOneFromWavelengthx2": KfSinusoidalEntangledZeroOneFromWavelengthx2,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx3": KfSinusoidalEntangledZeroOneFromWavelengthx3,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx4": KfSinusoidalEntangledZeroOneFromWavelengthx4,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx5": KfSinusoidalEntangledZeroOneFromWavelengthx5,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx6": KfSinusoidalEntangledZeroOneFromWavelengthx6,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx7": KfSinusoidalEntangledZeroOneFromWavelengthx7,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx8": KfSinusoidalEntangledZeroOneFromWavelengthx8,
+    "KfSinusoidalEntangledZeroOneFromWavelengthx9": KfSinusoidalEntangledZeroOneFromWavelengthx9,
+
+    "KfSinusoidalEntangledZeroOneFromFrequencyx2": KfSinusoidalEntangledZeroOneFromFrequencyx2,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx3": KfSinusoidalEntangledZeroOneFromFrequencyx3,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx4": KfSinusoidalEntangledZeroOneFromFrequencyx4,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx5": KfSinusoidalEntangledZeroOneFromFrequencyx5,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx6": KfSinusoidalEntangledZeroOneFromFrequencyx6,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx7": KfSinusoidalEntangledZeroOneFromFrequencyx7,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx8": KfSinusoidalEntangledZeroOneFromFrequencyx8,
+    "KfSinusoidalEntangledZeroOneFromFrequencyx9": KfSinusoidalEntangledZeroOneFromFrequencyx9,
+}
+
+# A dictionary that contains the friendly/humanly readable titles for the nodes
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "KfSinusoidalEntangledZeroOneFromWavelengthx2": "2x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx3": "3x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx4": "4x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx5": "5x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx6": "6x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx7": "7x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx8": "8x Entangled Curves [0,1] (Wavelength)",
+    "KfSinusoidalEntangledZeroOneFromWavelengthx9": "9x Entangled Curves [0,1] (Wavelength)",
+
+    "KfSinusoidalEntangledZeroOneFromFrequencyx2": "2x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx3": "3x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx4": "4x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx5": "5x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx6": "6x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx7": "7x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx8": "8x Entangled Curves [0,1] (Frequency)",
+    "KfSinusoidalEntangledZeroOneFromFrequencyx9": "9x Entangled Curves [0,1] (Frequency)",
+}
@@ -0,0 +1,406 @@
+import keyframed as kf
+#from keyframed.interpolation import bisect_left_keyframe, bisect_right_keyframe
+
+from functools import total_ordering
+from sortedcontainers import SortedDict, SortedList
+from .core import CATEGORY as RootCategory
+
+import numpy as np
+from numbers import Number
+
+import torch
+from copy import deepcopy
+import logging
+
+logging.basicConfig(level=logging.DEBUG, 
+                    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+CATEGORY=RootCategory + "/schedule"
+
+
+
+
+# @total_ordering
+# class ScheduleKeyframe(kf.Keyframe):
+#     def __lt__(self, other):
+#         return self.t < other
+
+
+# def update_schedule(schedule, keyframe):
+#     bl_idx = schedule.bisect_left(keyframe.t)
+#     try:
+#         if schedule[bl_idx].t == keyframe.t:
+#             #del schedule[bl_idx]
+#             schedule.pop(bl_idx)
+#     except IndexError:
+#         pass
+#     schedule.add(keyframe)
+#     return schedule
+
+
+
+
+
+# # scavenged from Keyframed...
+
+# def bisect_left_keyframe(k: Number, curve:SortedList, *args, **kargs) -> ScheduleKeyframe:
+#     """
+#     finds the value of the keyframe in a sorted dictionary to the left of a given key, i.e. performs "previous" interpolation
+#     """
+#     right_index = curve.bisect_right(k)
+#     left_index = right_index - 1
+#     #if right_index > 0:
+#     if right_index >= 0:
+#         #_, left_value = self._data.peekitem(left_index)
+#         left_value = curve[left_index]
+#     else:
+#         raise RuntimeError(
+#             "The return value of bisect_right should always be greater than zero, "
+#             f"however self._data.bisect_right({k}) returned {right_index}."
+#             "You should never see this error. Please report the circumstances to the library issue tracker on github."
+#             )
+#     return left_value
+
+
+# def bisect_right_keyframe(k: Number, curve:SortedList, *args, **kargs) -> ScheduleKeyframe:
+#     """
+#     finds the value of the keyframe in a sorted dictionary to the right of a given key, i.e. performs "next" interpolation
+#     """
+#     right_index = curve.bisect_right(k)
+#     #if right_index > 0:
+#     if right_index >= 0:
+#         #_, right_value = curve.peekitem(right_index)
+#         right_value = curve[right_index]
+#     else:
+#         raise RuntimeError(
+#             "The return value of bisect_right should always be greater than zero, "
+#             f"however self._data.bisect_right({k}) returned {right_index}."
+#             "You should never see this error. Please report the circumstances to the library issue tracker on github."
+#             )
+#     return right_value
+
+
+
+# schedule = SortedList()
+
+# x0 = ScheduleKeyframe(t=0, value="a")
+# x1 = ScheduleKeyframe(t=5, value="b")
+# x2 = ScheduleKeyframe(t=5, value="c")
+# x3 = ScheduleKeyframe(t=6, value="d")
+
+
+
+# schedule = update_schedule(schedule, x0)
+# schedule = update_schedule(schedule, x3) # 
+# schedule = update_schedule(schedule, x2)
+# schedule = update_schedule(schedule, x1)
+# schedule
+
+
+
+###################################################################################
+
+
+
+class KfKeyframedCondition:
+    """
+    Attaches a condition to a keyframe
+    """
+    CATEGORY=CATEGORY
+    FUNCTION = 'main'
+    RETURN_TYPES = ("KEYFRAMED_CONDITION",)
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "conditioning": ("CONDITIONING", {}),
+                "time": ("FLOAT", {"default": 0}), 
+                #"weight": ("FLOAT", {"default": 1}), # maybe i should hide this attribute
+                "interpolation_method": (list(kf.interpolation.INTERPOLATORS.keys()),),
+            },
+        }
+    
+    def main(self, conditioning, time, interpolation_method):
+        #keyframe = kf.Keyframe(t=time, value=weight, interpolation_method=interpolation_method)
+        #keyframe = ScheduleKeyframe(t=time, value=weight, interpolation_method=interpolation_method)
+        #return (keyframe, conditioning)
+        #kf_cond = ScheduleKeyframe(t=time, value=conditioning, interpolation_method=interpolation_method)
+        #return (kf_cond,)
+        ###########################
+
+        # separately create keyframes for the parts that need interpolating, and carry around anything else
+        cond_tensor, cond_dict = conditioning[0] # uh... i have NO idea what to do if there are multiple condition entries here... map over them i guess?
+        #cond_tensor = deepcopy(cond_tensor)
+        cond_tensor = cond_tensor.clone()
+        kf_cond_t = kf.Keyframe(t=time, value=cond_tensor, interpolation_method=interpolation_method)
+
+        cond_pooled = cond_dict.get("pooled_output")
+        cond_dict = deepcopy(cond_dict)
+        kf_cond_pooled = None
+        if cond_pooled is not None:
+            cond_pooled = cond_pooled.clone()
+            kf_cond_pooled = kf.Keyframe(t=time, value=cond_pooled, interpolation_method=interpolation_method)
+            cond_dict["pooled_output"] = cond_pooled
+        
+        return ({"kf_cond_t":kf_cond_t, "kf_cond_pooled":kf_cond_pooled, "cond_dict":cond_dict},)
+
+
+class KfSetKeyframe:
+    CATEGORY=CATEGORY
+    FUNCTION = 'main'
+    RETURN_TYPES = ("SCHEDULE",)
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "keyframed_condition": ("KEYFRAMED_CONDITION", {}),
+            },
+            "optional": {
+                "schedule": ("SCHEDULE", {}), 
+            }
+        }
+    def main(self, keyframed_condition, schedule=None):
+        #keyframe, kf_condition = keyframed_condition
+        cond_dict = keyframed_condition.pop("cond_dict")
+        cond_dict = deepcopy(cond_dict)
+
+        if schedule is None:
+            curve_tokenized = kf.Curve([keyframed_condition["kf_cond_t"]], label="kf_cond_t")
+            curves = [curve_tokenized]
+            if keyframed_condition["kf_cond_pooled"] is not None:
+                curve_pooled = kf.Curve([keyframed_condition["kf_cond_pooled"]], label="kf_cond_pooled")
+                curves.append(curve_pooled)
+            schedule = (kf.ParameterGroup(curves), cond_dict)
+            #schedule = kf.ParameterGroup(keyframed_condition) #parameters
+            #schedule = SortedList() #SortedDict
+            #schedule = kf.Curve([keyframed_condition])
+            #schedule = kf.Curve({keyframed_condition.t: keyframed_condition})
+        else:
+            schedule, old_cond_dict = schedule
+            for k, v in keyframed_condition.items():
+                if (v is not None):
+                    # for now, assume we already have a schedule for k.
+                    # Not sure how to handle new conditioning type appearing.
+                    schedule.parameters[k][v.t] = v
+            #schedule[keyframed_condition.t] = keyframed_condition
+            #schedule._data[keyframed_condition.t] = keyframed_condition
+            old_cond_dict.update(cond_dict) # NB: mutating this is probably bad
+            schedule = (schedule, old_cond_dict)
+
+        #schedule = update_schedule(schedule, keyframed_condition)
+        return (schedule,)
+
+def evaluate_schedule_at_time(schedule, time):
+    #schedule, cond_dict = schedule
+    schedule, cond_dict = schedule
+    #cond_dict = deepcopy(cond_dict)
+    values = schedule[time]
+    cond_t = values.get("kf_cond_t")
+    cond_pooled = values.get("kf_cond_pooled")
+    if cond_pooled is not None:
+        #cond_dict = deepcopy(cond_dict)
+        cond_dict["pooled_output"] = cond_pooled.clone()
+    logger.debug(f"type(cond_t):{type(cond_t)}")
+    logger.debug(f"type(cond_pooled):{type(cond_pooled)}")
+    logger.debug(f"type(cond_dict):{type(cond_dict)}")
+    return [(cond_t.clone(), cond_dict)]
+
+
+# def evaluate_schedule_at_time__OLD2(schedule, time):
+#     kf_cond_left, kf_cond_right = bisect_left_keyframe(time, schedule), bisect_right_keyframe(time, schedule)
+#     logger.debug(f"kf_cond_left: {kf_cond_left}")
+#     #return (kf_cond_left.value,)
+
+#     kf_tokenized_left = deepcopy(kf_cond_left)
+#     #kf_pooled_left = deepcopy(kf_cond_left)
+#     kf_tokenized_left.value = kf_cond_left.value[0]
+#     #kf_pooled_left.value = kf_cond_left.value[1].get("pooled_output")
+
+#     kf_tokenized_right = deepcopy(kf_cond_right)
+#     #kf_pooled_right = deepcopy(kf_cond_right)
+#     kf_tokenized_right.value = kf_cond_right.value[0]
+#     #kf_pooled_right.value = kf_cond_right.value[1].get("pooled_output")
+
+#     curve_tokenized = kf.Curve([kf_tokenized_left, kf_tokenized_right])
+#     #curve_pooled = kf.Curve([kf_pooled_left, kf_pooled_right])
+
+#     lerped_tokenized = curve_tokenized[time]
+#     logger.debug(lerped_tokenized)
+#     #lerped_pooled = curve_pooled[time]
+
+#     #out_dict = deepcopy(kf_cond_left.value[1])
+#     #out_dict["pooled_output"] = lerped_pooled
+#     out_dict={}
+
+#     return (lerped_tokenized, out_dict)
+
+
+def evaluate_schedule_at_time__OLD(schedule, time):
+    bl_idx = schedule.bisect_left(time)
+    logger.debug(f"bl_idx:{bl_idx}")
+    print(f"bl_idx:{bl_idx}")
+    #left_kf, left_cond = schedule[bl_idx]
+    left_kf = schedule[bl_idx]
+    left_cond = left_kf.value
+    if left_kf.t == time: # hit time exactly, return
+        #return (left_kf, left_cond)
+        return left_cond
+    if bl_idx == len(schedule): # there's nothing to our right, return
+        #return (left_kf, left_cond)
+        return left_cond
+    #right_kf, right_cond = schedule[bl_idx+1]
+    right_kf = schedule[bl_idx+1]
+    right_cond = right_kf.value
+    logger.info(f"type(right_kf):{type(right_kf)}")
+    logger.info(f"type(right_cond):{type(right_cond)}")
+    start, end = left_kf.t, right_kf.t
+    interval_length = end - start
+    elapsed = time-start
+    perc_complete = elapsed / interval_length
+    # TODO: use interpolation method on keyframe to compute transition weight
+    # For now, simple lerp
+
+    # TODO: This isn't a proper cond object. need to separately lerp the cond and the pooled output
+    #lerped_cond = perc_complete * right_cond + (1-perc_complete)*left_cond
+    right_tokenized, right_dict = right_cond
+    right_pooled = right_dict.get["pooled_output"]
+    logger.info(f"type(right_tokenized):{type(right_tokenized)}")
+    logger.info(f"type(right_pooled):{type(right_pooled)}")
+
+    left_tokenized, left_dict = left_cond
+    left_pooled = left_dict.get["pooled_output"]
+    logger.info(f"type(left_tokenized):{type(left_tokenized)}")
+    logger.info(f"type(left_pooled):{type(left_pooled)}")
+
+    lerped_tokenized = perc_complete * right_tokenized + (1-perc_complete)*left_tokenized
+    
+    # TODO: simplify this
+    if (right_pooled is not None) and (left_pooled is not None):
+        lerped_pooled = perc_complete * right_pooled + (1-perc_complete)*left_pooled
+    else:
+        if right_pooled is not None:
+            lerped_pooled = perc_complete * right_pooled
+        elif left_pooled is not None:
+            lerped_pooled = (1-perc_complete) * left_pooled
+    logger.info(f"type(lerped_pooled):{type(lerped_pooled)}")
+    out_dict = deepcopy(left_dict)
+    if lerped_pooled is not None:
+        out_dict['pooled_output'] = lerped_pooled
+
+    logger.info("type(lerped_tokenized):{type(lerped_tokenized)}")
+    # TODO: we could also interpolate and return an associated weight
+    return (lerped_tokenized, out_dict)
+
+
+class KfGetScheduleConditionAtTime:
+    CATEGORY=CATEGORY
+    FUNCTION = 'main'
+    RETURN_TYPES = ("CONDITIONING",)
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "schedule": ("SCHEDULE",{}),
+                "time": ("FLOAT",{}),
+            }
+        }
+    
+    def main(self, schedule, time):
+        lerped_cond = evaluate_schedule_at_time(schedule, time)
+        return (lerped_cond,)
+        
+
+
+class KfGetScheduleConditionSlice:
+    CATEGORY=CATEGORY
+    FUNCTION = 'main'
+    RETURN_TYPES = ("CONDITIONING",)
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "schedule": ("SCHEDULE",{}),
+                "start": ("FLOAT",{"default":0}),
+                #"stop": ("FLOAT",{"default":0}),
+                "step": ("FLOAT",{"default":1}),
+                "n": ("INT", {"default":24}),
+                #"endpoint": ("BOOL", {"default":True})
+            }
+        }
+    
+    #def main(self, schedule, start, stop, n, endpoint):
+    def main(self, schedule, start, step, n):
+        stop = start+n*step
+        times = np.linspace(start=start, stop=stop, num=n, endpoint=True)
+        conds = [evaluate_schedule_at_time(schedule, time)[0] for time in times]
+        lerped_tokenized = [c[0] for c in conds]
+        lerped_pooled = [c[1]["pooled_output"] for c in conds]
+        lerped_tokenized_t = torch.cat(lerped_tokenized, dim=0)
+        logger.info(f"lerped_tokenized_t.shape: {lerped_tokenized_t.shape}")
+        out_dict = deepcopy(conds[0][1])
+        if isinstance(lerped_pooled[0], torch.Tensor) and isinstance(lerped_pooled[-1], torch.Tensor):
+            out_dict['pooled_output'] =  torch.cat(lerped_pooled, dim=0)
+        return [[(lerped_tokenized_t, out_dict)]] # uh... wrap it in lists until it doesn't complain?
+
+###################################################################
+
+NODE_CLASS_MAPPINGS = {
+    "KfKeyframedCondition": KfKeyframedCondition,
+    "KfSetKeyframe": KfSetKeyframe,
+    "KfGetScheduleConditionAtTime": KfGetScheduleConditionAtTime,
+    "KfGetScheduleConditionSlice": KfGetScheduleConditionSlice,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {}
+
+
+###################################################################################
+
+# class KfSetKeyframe:
+#     CATEGORY=CATEGORY
+#     FUNCTION = 'main'
+#     RETURN_TYPES = ("SCHEDULE",)
+    
+#     @classmethod
+#     def INPUT_TYPES(cls):
+#         return {
+#             "required": {
+#                 "keyframed_condition": ("KEYFRAMED_CONDITION", {}),
+#             },
+#             "optional": {
+#                 "schedule": ("SCHEDULE", {}), 
+#             }
+#         }
+#     def main(keyframed_condition, schedule=None):
+#         keyframe, kf_condition = keyframed_condition
+#         if schedule is None:
+#             schedule = SortedDict
+#         schedule[keyframe.t] = keyframed_condition
+#         return (schedule,)
+
+# class KfGetScheduleConditionAtTime:
+#     CATEGORY=CATEGORY
+#     FUNCTION = 'main'
+#     RETURN_TYPES = ("KEYFRAME",)
+
+#     @classmethod
+#     def INPUT_TYPES(cls):
+#         return {
+#             "required": {
+#                 "schedule": ("SCHEDULE",{}),
+#                 "time": ("FLOAT",{}),
+#             }
+#         }
+    
+#     def main(self, schedule, time):
+        
+#         # right_index = self._data.bisect_right(k)
+#         # left_index = right_index - 1
+#         # if right_index > 0:
+#         #     _, left_value = self._data.peekitem(left_index)
+#         # else: