class_docstr: Holds the param-space coordinates (X) and target values (Y)
  
  Parameters
  ----------
  pbounds : dict
      Dictionary with parameters names and legal values.
  
  random_state : int, RandomState, or None
      optionally specify a seed for a random number generator, by default None.
class_docstr_tok: ["Holds","the","param-space","coordinates","(","X",")","and","target","values","(","Y",")","Parameters","--","--","--","--","--","pbounds",":","dict","Dictionary","with","parameters","names","and","legal","values",".","random_state",":","int",",","RandomState",",","or","None","optionally","specify","a","seed","for","a","random","number","generator",",","by","default","None","."]
docstr: length of registered params and targets
  
  Returns
  -------
  int
docstr_tok: ["length","of","registered","params","and","targets","Returns","--","--","--","-","int"]
code: def len(self):
      """
      length of registered params and targets
  
      Returns
      -------
      int
      """
      assert len(self._params) == len(self._target)
      return len(self._target)
  
file_path: nni/nni/algorithms/hpo/gp_tuner/target_space.py
imports: import numpy
  import nni.parameter_expressions
label_desc: Use image node_id 3 for calling the TargetSpace obj's underlying member method code with example usage: obj.len() and returns: len