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
