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# Adapted from: https://github.com/binghong-ml/retro_star
import numpy as np
import logging
class ReactionNode:
def __init__(self, parent, cost, template, analysis_tokens):
self.parent = parent
self.depth = self.parent.depth + 1
self.id = -1
self.cost = cost
self.template = template
self.analysis_tokens = analysis_tokens
self.children = []
self.value = None # [V(m | subtree_m) for m in children].sum() + cost
self.succ_value = np.inf # total cost for existing solution
self.target_value = None # V_target(self | whole tree)
self.succ = None # successfully found a valid synthesis route
self.open = True # before expansion: True, after expansion: False
parent.children.append(self)
def v_self(self):
"""
:return: V_self(self | subtree)
"""
return self.value
def v_target(self):
"""
:return: V_target(self | whole tree)
"""
return self.target_value
def init_values(self):
assert self.open
self.value = self.cost
self.succ = True
for mol in self.children:
self.value += mol.value
self.succ &= mol.succ
if self.succ:
self.succ_value = self.cost
for mol in self.children:
self.succ_value += mol.succ_value
self.target_value = self.parent.v_target() - self.parent.v_self() + \
self.value
self.open = False
def backup(self, v_delta, from_mol=None):
self.value += v_delta
self.target_value += v_delta
self.succ = True
for mol in self.children:
self.succ &= mol.succ
if self.succ:
self.succ_value = self.cost
for mol in self.children:
self.succ_value += mol.succ_value
if v_delta != 0:
assert from_mol
self.propagate(v_delta, exclude=from_mol)
return self.parent.backup(self.succ)
def propagate(self, v_delta, exclude=None):
if exclude is None:
self.target_value += v_delta
for child in self.children:
if exclude is None or child.mol != exclude:
for grandchild in child.children:
grandchild.propagate(v_delta)
def serialize(self):
return '%d' % (self.id) |