class_docstr: Tuner with genetic algorithm.
  This tuner does not have a cost model so it always run measurement on real machines.
  This tuner expands the :code:`ConfigEntity` as gene.
  
  Parameters
  ----------
  pop_size: int
      number of genes in one generation
  elite_num: int
      number of elite to keep
  mutation_prob: float
      probability of mutation of a knob in a gene
code: def load_history(self, data_set, min_seed_records=500):
      pass
  
file_path: tvm/python/tvm/autotvm/tuner/ga_tuner.py
imports: import numpy
  from .tuner import Tuner
label_desc: Use image node_id 5 for calling the GATuner obj's underlying member method code with example usage: obj.load_history(data_set, min_seed_records) without return types