# @Time : 2018/1/17 PM4:30
# @Author : Shiloh Leung
# @Site :
# @File : ml_ncp.py
# @Software: PyCharm Community Edition
from tensorD.dataproc.reader import TensorReader
import tensorflow as tf
from tensorD.factorization.env import Environment
from tensorD.dataproc.provider import Provider
from tensorD.factorization.ncp import NCP_BCU
from tensorD.demo.DataGenerator import *
if __name__ == '__main__':
full_shape = [943, 1682, 31]
base = TensorReader('/root/tensorD_f/data_out_tmp/u1.base.csv')
base.read(full_shape=full_shape)
with tf.Session() as sess:
rating_tensor = sess.run(base.full_data)
data_provider = Provider()
data_provider.full_tensor = lambda: rating_tensor
env = Environment(data_provider, summary_path='/tmp/ncp_ml')
ncp = NCP_BCU(env)
args = NCP_BCU.NCP_Args(rank=20, validation_internal=1)
ncp.build_model(args)
loss_hist = ncp.train(100)
out_path = '/root/tensorD_f/data_out_tmp/python_out/ncp_ml_20.txt'
with open(out_path, 'w') as out:
for loss in loss_hist:
out.write('%.6f\n' % loss)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2017/8/6 PM3:31
# @Author : Shiloh Leung
# @Site :
# @File : reader_test.py
# @Software: PyCharm Community Edition
from tensorD.dataproc.reader import TensorReader
import time
import tensorflow as tf
if __name__ == '__main__':
print('csv file:')
file_path = 'data1.csv'
treader = TensorReader(file_path)
start = time.time()
treader.read()
end = time.time()
print('reader time: %.6f s\n' % (end - start))
with tf.Session() as sess:
print(sess.run(treader.sparse_data))
print(sess.run(treader.full_data))