def train_candidate_model(model: CandidateModel, process: ElectionConstructor,
population: NDPopulation, max_steps: int):
timings = Timings()
stats = ModelStats()
first = True
while model.global_step < max_steps:
winner, candidates, balance = run_sample_election(
model, process, population, True)
for i in range(len(candidates)):
model.add_sample_from_candidates(candidates[i], candidates[0:i],
winner)
if model.ready():
if first:
print("starting to train")
first = False
stats.update(winner, candidates, balance)
for i in range(5):
with timings.time_block("model.train"):
model.train(128)
if model.global_step % 1000 == 0:
stats.print(process.name, model.global_step)
if model.global_step < max_steps:
stats.reset()
timings.print()
