# HG changeset patch
# User Arnaud Bergeron <abergeron@gmail.com>
# Date 1269645483 14400
# Node ID d89820070ea0048506911b17f0c243a31a6b51ce
# Parent  8108d271c30c57eefadc660f64435575aa524c6d
Add some prints to see the current step.

diff -r 8108d271c30c -r d89820070ea0 deep/convolutional_dae/run_exp.py
--- a/deep/convolutional_dae/run_exp.py	Fri Mar 26 18:49:27 2010 -0400
+++ b/deep/convolutional_dae/run_exp.py	Fri Mar 26 19:18:03 2010 -0400
@@ -9,6 +9,7 @@
     from ift6266.deep.convolutional_dae.sgd_opt import sgd_opt
     import pylearn, theano, ift6266
     import pylearn.version
+    import sys
 
     # params: bsize, pretrain_lr, train_lr, nfilts1, nfilts2, nftils3, nfilts4
     #         pretrain_rounds, noise, mlp_sz
@@ -17,7 +18,7 @@
     # TODO: maybe record pynnet version?
     channel.save()
 
-    dset = datasets.nist_all(1000)
+    dset = datasets.nist_digits()
 
     nfilts = []
     if state.nfilts1 != 0:
@@ -53,11 +54,15 @@
 
     series = create_series()
 
+    print "pretraining ..."
+    sys.stdout.flush()
     do_pretrain(pretrain_fs, state.pretrain_rounds, series['recons_error'])
 
+    print "training ..."
+    sys.stdout.flush()
     sgd_opt(train, valid, test, training_epochs=100000, patience=10000,
             patience_increase=2., improvement_threshold=0.995,
-            validation_frequency=2500, series=series, net=net)
+            validation_frequency=1000, series=series, net=net)
 
 if __name__ == '__main__':
     st = dumb()