code: def generate_trials_to_calculate(points):
      """
      Function that generates trials to be evaluated from list of points
  
      :param points: List of points to be inserted in trials object in form of
          dictionary with variable names as keys and variable values as dict
          values. Example value:
          [{'x': 0.0, 'y': 0.0}, {'x': 1.0, 'y': 1.0}]
  
      :return: object of class base.Trials() with points which will be calculated
          before optimisation start if passed to fmin().
      """
      trials = base.Trials()
      new_trials = [
          generate_trial(tid, x) for tid, x in enumerate(points)
      ]
      trials.insert_trial_docs(new_trials)
      return trials
  
imports: import functools
  import inspect
  import logging
  import os
  import sys
  import time
  from timeit import default_timer
  import numpy
  from hyperopt import tpe, exceptions
  from hyperopt.base import validate_timeout, validate_loss_threshold
  from .None import pyll
  from .utils import coarse_utcnow
  from .None import base
  from .None import progress
label_desc: Use image node_id 2 for calling a global function with example usage: generate_trials_to_calculate(points) and returns: trials