def main():
cards_path = setting_exp.get('cards')
field_vocabulary_path = setting_exp.get('field_vocabulary_path')
spymaster_vocabulary_path = setting_exp.get('spymaster_vocabulary_path')
keep_similarities_table = setting_exp.getint('keep_similarities_table')
metrics_path = os.path.join(log_dir_path, "metrics.json")
penalize_negative = setting_exp.getint('add_penalize_negative_for_clue_score')
normalize_negative = setting_exp.getint('normalize_negative_for_score')
# if not normalize_negative:
# normalize_negative = 0
games_averaging = setup_averaging()
wv_noise_std_range = setup_noise_params()
threshold_delta_range = setup_threshold_delta()
alpha_range = setup_alpha()
# load embeddings.
embeddings_spymaster, embeddings_guesser = setup_embeddings()
# Create field, not initialized with cards yet.
field = Field(field_logger, metrics_path, vocabulary_path=field_vocabulary_path)
for game_count in range(games_averaging):
# generate the field.
similarities_table_path = os.path.join(model_dir_path, "game{}.pkl".format(game_count))
field.generate_cards()
for wv_noise_std in wv_noise_std_range:
# prepare dict for guesser
noised_embeddings_dict = add_noise(model=embeddings_guesser, mean=0, std=wv_noise_std) # seems to be super slow, TBD
field.logger.info("------Noise std set to {0:.2f}.-------\n".format(wv_noise_std))
for threshold_delta in threshold_delta_range:
field.logger.info("------Delta set to {0:.3f}.-------\n".format(threshold_delta))
# For each noise level, play multiple games on different fields.
for alpha in alpha_range:
field.reset_scores()
field.logger.info("------Alpha set to {0:.3f}.-------\n".format(alpha))
play_one_game(field, embeddings_spymaster, noised_embeddings_dict, spymaster_vocabulary_path,
keep_similarities_table, similarities_table_path, threshold_delta, penalize_negative,
normalize_negative, alpha, field_logger, team_logger,
game_count)
# Play games with different noise level.
multiple_game_metrics = {"RED": defaultdict(list), "BLUE": defaultdict(list)}
hparams = {"hparams_alpha": alpha,
"hparams_delta": threshold_delta,
"hparams_noise": wv_noise_std,
"game_count": game_count+1
}
for key, val in hparams.items():
multiple_game_metrics.update({key: val})
multiple_game_metrics = field.append_game_metrics(multiple_game_metrics)
# Dump metrics of the games along with the hparams.
field.dump_external_metrics(multiple_game_metrics)
'''
