Question about running logistic_cg.py #73
Description
When I run the logistic_cg.py, I got these:
logistic_cg
... lThe code for file logistic_cg.py ran for 33.5s
The code for file mlp.py ran for 0.92m
The code for file convolutional_mlp.py ran for 0.82m
The no corruption code for file dA.py ran for 0.72m
The 30% corruption code for file dA.py ran for 0.73m
The pretraining code for file SdA.py ran for 1.84m
oading data
... building the model
Optimizing using scipy.optimize.fmin_cg...
validation error 29.989583 %
validation error 24.437500 %
validation error 20.760417 %
validation error 16.937500 %
validation error 14.270833 %
validation error 14.156250 %
validation error 13.177083 %
validation error 12.270833 %
validation error 11.697917 %
validation error 11.531250 %
validation error 10.531250 %
validation error 10.385417 %
validation error 10.135417 %
validation error 10.260417 %
validation error 9.885417 %
validation error 9.791667 %
validation error 9.208333 %
validation error 9.010417 %
validation error 8.937500 %
validation error 8.833333 %
validation error 8.760417 %
validation error 8.510417 %
validation error 8.354167 %
validation error 8.229167 %
validation error 8.270833 %
validation error 8.062500 %
validation error 7.979167 %
validation error 7.895833 %
validation error 7.875000 %
validation error 8.052083 %
Optimization complete with best validation score of 7.875000 %, with test performance 7.822917 %
The code run for 30 epochs in 0.559m, with 0.894673 epochs/sec
My question is that I don't know what these outputs mean:
"
... lThe code for file logistic_cg.py ran for 33.5s
The code for file mlp.py ran for 0.92m
The code for file convolutional_mlp.py ran for 0.82m
The no corruption code for file dA.py ran for 0.72m
The 30% corruption code for file dA.py ran for 0.73m
The pretraining code for file SdA.py ran for 1.84m
oading data
"
Is there something wrong with these output?