return #======================================= ########################################################################## train_samples = mm.load_train_data(params['TRAIN_FILE']) char_dict, ord_dict = mm.build_vocab(train_samples) NUM_EMB = len(char_dict) DATA_LENGTH = max(map(len, train_samples)) MAX_LENGTH = params["MAX_LENGTH"] to_use = [ sample for sample in train_samples if mm.verified_and_below(sample, MAX_LENGTH) ] positive_samples = [ mm.encode(sample, MAX_LENGTH, char_dict) for sample in to_use ] POSITIVE_NUM = len(positive_samples) print('Starting ObjectiveGAN for {:7s}'.format(PREFIX)) print('Data points in train_file {:7d}'.format(len(train_samples))) print('Max data length is {:7d}'.format(DATA_LENGTH)) print('Max length to use is {:7d}'.format(MAX_LENGTH)) print('Avg length to use is {:7f}'.format( np.mean([len(s) for s in to_use]))) print('Num valid data points is {:7d}'.format(POSITIVE_NUM)) print('Size of alphabet is {:7d}'.format(NUM_EMB)) mm.print_params(params) ##########################################################################
mean_r, std_r = np.mean(rewards), np.std(rewards) min_r, max_r = np.min(rewards), np.max(rewards) print('Mean: {:.3f} , Std: {:.3f}'.format(mean_r, std_r),end='') print(', Min: {:.3f} , Max: {:.3f}\n'.format(min_r, max_r)) np.set_printoptions(precision=8, suppress=False) return #======================================= ########################################################################## train_samples = mm.load_train_data(params['TRAIN_FILE']) char_dict, ord_dict = mm.build_vocab(train_samples) NUM_EMB = len(char_dict) DATA_LENGTH = max(map(len, train_samples)) MAX_LENGTH = params["MAX_LENGTH"] to_use = [sample for sample in train_samples if mm.verified_and_below( sample, MAX_LENGTH)] positive_samples = [mm.encode(sample, MAX_LENGTH, char_dict) for sample in to_use] POSITIVE_NUM = len(positive_samples) print('Starting ObjectiveGAN for {:7s}'.format(PREFIX)) print('Data points in train_file {:7d}'.format(len(train_samples))) print('Max data length is {:7d}'.format(DATA_LENGTH)) print('Max length to use is {:7d}'.format(MAX_LENGTH)) print('Avg length to use is {:7f}'.format( np.mean([len(s) for s in to_use]))) print('Num valid data points is {:7d}'.format(POSITIVE_NUM)) print('Size of alphabet is {:7d}'.format(NUM_EMB)) mm.print_params(params) ##########################################################################