code: def run(c, gamma):
      iris = datasets.load_iris()
      per = permutation(iris.target.size)
      iris.data = iris.data[per]
      iris.target = iris.target[per]
      clf = svm.SVC(C=c, kernel="rbf", gamma=gamma)
      clf.fit(iris.data[:90], iris.target[:90])
      return clf.score(iris.data[90:], iris.target[90:])
  
imports: from numpy.random import permutation
  from sacred import Experiment
  from sklearn import datasets, svm
  from wandb.sacred import WandbObserver
label_desc: Use image node_id 2 for calling a global function with example usage: run(c, gamma) and returns: clf