code: def many_dists():
      a = hp.choice("a", [0, 1, 2])
      b = hp.randint("b", 10)
      bb = hp.randint("bb", 12, 25)
      c = hp.uniform("c", 4, 7)
      d = hp.loguniform("d", -2, 0)
      e = hp.quniform("e", 0, 10, 3)
      f = hp.qloguniform("f", 0, 3, 2)
      g = hp.normal("g", 4, 7)
      h = hp.lognormal("h", -2, 2)
      i = hp.qnormal("i", 0, 10, 2)
      j = hp.qlognormal("j", 0, 2, 1)
      k = hp.pchoice("k", [(0.1, 0), (0.9, 1)])
      z = a + b + bb + c + d + e + f + g + h + i + j + k
      return {
          "loss": scope.float(scope.log(1e-12 + z**2)),
          "status": base.STATUS_OK,
      }
  
imports: import unittest
  import numpy
  from hyperopt import Trials, Domain, fmin, hp, base
  from hyperopt.rand import suggest
  from hyperopt.pyll import as_apply
  from hyperopt.pyll import scope
label_desc: Use image node_id 10 for calling a global function with example usage: many_dists() and returns: dict