class_docstr: Iterate over a set of fully-specified hyperparameter combinations.
  
  Args:
      hp_iter (list): list of fully-specified hyperparameter dicts. 
class_docstr_tok: ["Iterate","over","a","set","of","fully-specified","hyperparameter","combinations",".","Args",":","hp_iter","(","list",")",":","list","of","fully-specified","hyperparameter","dicts","."]
docstr: Computes list of parameter objects from list of hyperparameter
  combinations, which is needed for initializing a Study.
  
  Returns:
      list: List of Parameter objects.
docstr_tok: ["Computes","list","of","parameter","objects","from","list","of","hyperparameter","combinations",",","which","is","needed","for","initializing","a","Study",".","Returns",":","list",":","List","of","Parameter","objects","."]
code: def get_parameters(self):
      """
      Computes list of parameter objects from list of hyperparameter
      combinations, which is needed for initializing a Study.
  
      Returns:
          list: List of Parameter objects.
      """
      parameters = []
      keys = self.hp_iter[0].keys()
      for pname in keys:
          # Get unique values of this (possibly unhashable) parameter.
          prange = []
          for i, hp in enumerate(self.hp_iter):
              if pname not in hp:
                  raise Exception(
                      "Parameter {} not found in list item {}.".format(
                          pname, i
                      )
                  )
              value = hp[pname]
              if value not in prange:
                  prange.append(value)
          p = sherpa.Parameter.from_dict(
              {"name": pname, "type": "choice", "range": prange}
          )
          parameters.append(p)
      return parameters
  
imports: import os
  import random
  import numpy
  import logging
  import sherpa
  import pandas
  import sklearn.gaussian_process
  from sherpa.core import Choice, Continuous, Discrete, Ordinal, AlgorithmState
  from sherpa.core import rng
  import sklearn.model_selection
  import collections
label_desc: Use image node_id 4 for calling the Iterate obj's underlying member method code with example usage: obj.get_parameters() and returns: parameters