Esempi in Python per load_all_query_url

Esempio n. 1

File: train_16.py Progetto: zjmonk/UGACH

D_LEARNING_RATE = 0.001
G_LEARNING_RATE = 0.01
BETA = OUTPUT_DIM / 8.0
GAMMA = 0.1

WORKDIR = '../mir/'
GEN_MODEL_BEST_FILE = './model/gan_best_nn_' + str(OUTPUT_DIM) + '.model'
DIS_MODEL_BEST_FILE = './model/dis_best_nn_' + str(OUTPUT_DIM) + '.model'

GEN_MODEL_NEWEST_FILE = './model/gan_newest_nn_' + str(OUTPUT_DIM) + '.model'
DIS_MODEL_NEWEST_FILE = './model/dis_newest_nn_' + str(OUTPUT_DIM) + '.model'

DIS_MODEL_PRETRAIN_FILE = './model/dis_pretrain_nn_' + str(
    OUTPUT_DIM) + '.model'

train_i2t, train_i2t_pos, train_i2t_neg, train_t2i, train_t2i_pos, train_t2i_neg, test_i2t, test_i2t_pos, test_t2i, test_t2i_pos = ut.load_all_query_url(
    WORKDIR + 'list/', CLASS_DIM)

feature_dict = ut.load_all_feature(WORKDIR + 'list/', WORKDIR + 'feature/')
label_dict = ut.load_all_label(WORKDIR + 'list/')

record_file = open('record_' + str(OUTPUT_DIM) + '.txt', 'w')
record_file.close()


def generate_samples(sess, generator, train_list, train_pos, train_neg, flag):
    data = []
    for query in train_pos:
        pos_list = train_pos[query]
        candidate_neg_list = train_neg[query]
        candidate_list = train_list[query]

Esempio n. 2

HIDDEN_DIM = 8192
CLASS_DIM = 24
BATCH_SIZE = 256
WEIGHT_DECAY = 0.01
D_LEARNING_RATE = 0.01
LAMBDA = 0
BETA = OUTPUT_DIM / 8.0
GAMMA = 0.1

# WORKDIR = '../mir/'
DIS_MODEL_BEST_FILE = '/....../teacher_best_pretrain' + str(
    OUTPUT_DIM) + '.model'
#DIS_MODEL_BEST_I2I_FILE = '/home/huhengtong/UKD/teacher_UGACH/OL_teacher_best_i2i_' + str(OUTPUT_DIM) + '.model'
# DIS_MODEL_NEWEST_FILE = './model/dis_newest_nn_' + str(OUTPUT_DIM) + '.model'

train_i2t, train_i2t_pos, train_i2t_neg, train_t2i, train_t2i_pos, train_t2i_neg = ut.load_all_query_url(
)

# pdb.set_trace()

feature_dict = ut.load_all_feature()
label_dict = ut.load_all_label()
#print(len(feature_dict), len(label_dict))


def generate_samples(train_pos, train_neg, flag):
    data = []
    for query in train_pos:
        pos_list = train_pos[query]
        candidate_neg_list = train_neg[query]

        random.shuffle(pos_list)

Esempio n. 3

File: train_argv.py Progetto: zhushaoquan/MGAH_TMM2019

CLASS_DIM = 20
MODAL_NUM = 5
TRAIN_NUM = 4000
BATCH_SIZE = 16
WEIGHT_DECAY = 0.0005
D_LEARNING_RATE = 0.01
LAMBDA = 0
BETA = 1.0
GAMMA = 0.1

WORKDIR = '../xmedia/'
DIS_MODEL_BEST_FILE = './model/dis_best_nn_' + str(OUTPUT_DIM) + '.model'
DIS_MODEL_NEWEST_FILE = './model/dis_newest_nn_' + str(OUTPUT_DIM) + '.model'

#test_feature,database_feature,test_label,database_label = ut.load_all_query_url(WORKDIR + 'feature/',WORKDIR + 'list/', CLASS_DIM)
test_feature, database_feature, test_label, database_label = ut.load_all_query_url(
    WORKDIR + 'feature_znorm/', WORKDIR + 'list/', CLASS_DIM)

# pdb.set_trace()

train_feature = ut.load_train_feature(WORKDIR + 'feature_znorm/')
# label_dict = ut.load_all_label(WORKDIR + 'list/')
knn_idx = ut.load_knn(WORKDIR + 'python/xmedia/')

#
record_file_name = 'record_' + str(OUTPUT_DIM) + '.txt',
#record_file = open('record_' + str(OUTPUT_DIM) + '.txt', 'w')
#record_file.close()


def generate_samples(fix):
    data = []