from eval.precision import precision_at_k from eval.ndcg import ndcg_at_k FEATURE_SIZE = 46 HIDDEN_SIZE = 46 WEIGHT_DECAY = 0.01 G_LEARNING_RATE = 0.001 TEMPERATURE = 0.2 workdir = 'MQ2008-semi' GAN_MODEL_BEST_FILE = workdir + '/gan/gan_best_nn.model' query_url_feature, _, _ =\ ut.load_all_query_url_feature(workdir + '/Large_norm.txt', FEATURE_SIZE) query_pos_train = ut.get_query_pos(workdir + '/train.txt') query_pos_test = ut.get_query_pos(workdir + '/test.txt') param_best = cPickle.load(open(GAN_MODEL_BEST_FILE)) assert param_best is not None generator_best = GEN(FEATURE_SIZE, HIDDEN_SIZE, WEIGHT_DECAY, G_LEARNING_RATE, temperature=TEMPERATURE, param=param_best) config = tf.ConfigProto() config.gpu_options.allow_growth = True sess = tf.Session(config=config) sess.run(tf.initialize_all_variables()) p_1_best = precision_at_k(sess, generator_best, query_pos_test, query_pos_train, query_url_feature, k=1) p_3_best = precision_at_k(sess, generator_best, query_pos_test, query_pos_train, query_url_feature, k=3)
#---------------------------------------------- # -*- encoding=utf-8 -*- # # __author__:'焉知飞鱼' # # CreateTime: # # 2020/7/13 11:50 # # # # 天下风云出我辈, # # 一入江湖岁月催。 # # 皇图霸业谈笑中, # # 不胜人生一场醉。 # #---------------------------------------------- import utils as ut workdir = 'MQ2008-semi' query_url_feature, query_url_index, query_index_url = \ ut.load_all_query_url_feature(workdir + '/Large_norm.txt', 46) query_pos_train = ut.get_query_pos(workdir + '/train.txt') # rank>0