code: def _filter_canopy_predicates(
      predicates: Iterable[Predicate], canopies: bool
  ) -> set[Predicate]:
      result = set()
      for predicate in predicates:
          if hasattr(predicate, "index"):
              is_canopy = hasattr(predicate, "canopy")
              if is_canopy == canopies:
                  result.add(predicate)
          else:
              result.add(predicate)
      return result
  
imports: from __future__ import annotations
  import logging
  import random
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, overload
  from warnings import warn
  import numpy
  import numpy.typing
  import sklearn.linear_model
  import dedupe.core
  import dedupe.training
label_desc: Use image node_id 1 for calling a global function with example usage: _filter_canopy_predicates(predicates, canopies) and returns: result