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In [1]:



    


from util import CSVLogger

logger = CSVLogger("../log/test.csv", 3)



    











In [2]:



    


%ls ../log



    


















    






mnist-cnn-2.csv  mnist-cnn-3.csv  test.csv

















In [3]:



    


%cat ../log/test.csv



    


















    






2016-07-19 20:36:32,788,Tag Name,Iteration,Minibatch Loss,Training Accuracy,Elapsed Time,Testing Accuracy,L1,L2,L3
2016-07-19 20:36:34,224,test,0,0.000000,0.00000,1.02,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,1,0.000000,10.00000,2.86e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,2,0.000000,20.00000,1.19e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,3,0.000000,30.00000,2.86e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,4,0.000000,40.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,5,0.000000,50.00000,0,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,6,0.000000,60.00000,1.19e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,7,0.000000,70.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,8,0.000000,80.00000,0,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,9,0.000000,90.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,,,,,100,['NA', 'NA', 'NA']
2016-07-19 20:37:42,092,test,0,0.000000,0.00000,67.9,1,2,3
2016-07-19 20:37:42,092,test,1,0.000000,10.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,2,0.000000,20.00000,2.86e-06,1,2,3
2016-07-19 20:37:42,113,test,3,0.000000,30.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,4,0.000000,40.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,5,0.000000,50.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,6,0.000000,60.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,7,0.000000,70.00000,0,1,2,3
2016-07-19 20:37:42,113,test,8,0.000000,80.00000,0,1,2,3
2016-07-19 20:37:42,113,test,9,0.000000,90.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,,,,,100,1,2,3

















In [4]:



    


logger.setTimer()



    











In [5]:



    


# sleep 1 sec.
import time
time.sleep(1)



    











In [6]:



    


for i in range(10) :
    logger.measure('test', i, 0, i*10)
logger.accuracy('test', 100)



    











In [7]:



    


%cat ../log/test.csv



    


















    






2016-07-19 20:36:32,788,Tag Name,Iteration,Minibatch Loss,Training Accuracy,Elapsed Time,Testing Accuracy,L1,L2,L3
2016-07-19 20:36:34,224,test,0,0.000000,0.00000,1.02,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,1,0.000000,10.00000,2.86e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,2,0.000000,20.00000,1.19e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,3,0.000000,30.00000,2.86e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,4,0.000000,40.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,5,0.000000,50.00000,0,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,6,0.000000,60.00000,1.19e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,7,0.000000,70.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,8,0.000000,80.00000,0,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,9,0.000000,90.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,,,,,100,['NA', 'NA', 'NA']
2016-07-19 20:37:42,092,test,0,0.000000,0.00000,67.9,1,2,3
2016-07-19 20:37:42,092,test,1,0.000000,10.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,2,0.000000,20.00000,2.86e-06,1,2,3
2016-07-19 20:37:42,113,test,3,0.000000,30.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,4,0.000000,40.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,5,0.000000,50.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,6,0.000000,60.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,7,0.000000,70.00000,0,1,2,3
2016-07-19 20:37:42,113,test,8,0.000000,80.00000,0,1,2,3
2016-07-19 20:37:42,113,test,9,0.000000,90.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,,,,,100,1,2,3
2016-07-19 20:40:00,098,test,0,0.000000,0.00000,1.02,NA,NA,NA
2016-07-19 20:40:00,101,test,1,0.000000,10.00000,8.01e-05,NA,NA,NA
2016-07-19 20:40:00,101,test,2,0.000000,20.00000,2.15e-06,NA,NA,NA
2016-07-19 20:40:00,101,test,3,0.000000,30.00000,1.1e-05,NA,NA,NA
2016-07-19 20:40:00,101,test,4,0.000000,40.00000,9.54e-07,NA,NA,NA
2016-07-19 20:40:00,101,test,5,0.000000,50.00000,9.54e-07,NA,NA,NA
2016-07-19 20:40:00,101,test,6,0.000000,60.00000,0,NA,NA,NA
2016-07-19 20:40:00,101,test,7,0.000000,70.00000,0,NA,NA,NA
2016-07-19 20:40:00,101,test,8,0.000000,80.00000,9.54e-07,NA,NA,NA
2016-07-19 20:40:00,101,test,9,0.000000,90.00000,1.19e-06,NA,NA,NA
2016-07-19 20:40:00,102,test,,,,,100,NA,NA,NA

















In [8]:



    


logger.setLayers(1, 2, 3)



    











In [9]:



    


for i in range(10) :
    logger.measure('test', i, i*10)



    











In [10]:



    


%cat ../log/test.csv



    


















    






2016-07-19 20:36:32,788,Tag Name,Iteration,Minibatch Loss,Training Accuracy,Elapsed Time,Testing Accuracy,L1,L2,L3
2016-07-19 20:36:34,224,test,0,0.000000,0.00000,1.02,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,1,0.000000,10.00000,2.86e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,2,0.000000,20.00000,1.19e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,224,test,3,0.000000,30.00000,2.86e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,4,0.000000,40.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,5,0.000000,50.00000,0,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,6,0.000000,60.00000,1.19e-06,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,7,0.000000,70.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,8,0.000000,80.00000,0,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,9,0.000000,90.00000,9.54e-07,['NA', 'NA', 'NA']
2016-07-19 20:36:34,225,test,,,,,100,['NA', 'NA', 'NA']
2016-07-19 20:37:42,092,test,0,0.000000,0.00000,67.9,1,2,3
2016-07-19 20:37:42,092,test,1,0.000000,10.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,2,0.000000,20.00000,2.86e-06,1,2,3
2016-07-19 20:37:42,113,test,3,0.000000,30.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,4,0.000000,40.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,5,0.000000,50.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,6,0.000000,60.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,7,0.000000,70.00000,0,1,2,3
2016-07-19 20:37:42,113,test,8,0.000000,80.00000,0,1,2,3
2016-07-19 20:37:42,113,test,9,0.000000,90.00000,9.54e-07,1,2,3
2016-07-19 20:37:42,113,test,,,,,100,1,2,3
2016-07-19 20:40:00,098,test,0,0.000000,0.00000,1.02,NA,NA,NA
2016-07-19 20:40:00,101,test,1,0.000000,10.00000,8.01e-05,NA,NA,NA
2016-07-19 20:40:00,101,test,2,0.000000,20.00000,2.15e-06,NA,NA,NA
2016-07-19 20:40:00,101,test,3,0.000000,30.00000,1.1e-05,NA,NA,NA
2016-07-19 20:40:00,101,test,4,0.000000,40.00000,9.54e-07,NA,NA,NA
2016-07-19 20:40:00,101,test,5,0.000000,50.00000,9.54e-07,NA,NA,NA
2016-07-19 20:40:00,101,test,6,0.000000,60.00000,0,NA,NA,NA
2016-07-19 20:40:00,101,test,7,0.000000,70.00000,0,NA,NA,NA
2016-07-19 20:40:00,101,test,8,0.000000,80.00000,9.54e-07,NA,NA,NA
2016-07-19 20:40:00,101,test,9,0.000000,90.00000,1.19e-06,NA,NA,NA
2016-07-19 20:40:00,102,test,,,,,100,NA,NA,NA
2016-07-19 20:40:00,326,test,0,0.000000,0.00000,0.224,1,2,3
2016-07-19 20:40:00,326,test,1,0.000000,10.00000,2.15e-06,1,2,3
2016-07-19 20:40:00,326,test,2,0.000000,20.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,3,0.000000,30.00000,1.91e-06,1,2,3
2016-07-19 20:40:00,327,test,4,0.000000,40.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,5,0.000000,50.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,6,0.000000,60.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,7,0.000000,70.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,8,0.000000,80.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,9,0.000000,90.00000,9.54e-07,1,2,3
2016-07-19 20:40:00,327,test,,,,,100,1,2,3

Content source: hyunghunny/tf-hpo

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