--- a/deep/stacked_dae/utils.py	Tue Mar 02 14:47:18 2010 -0500
+++ b/deep/stacked_dae/utils.py	Wed Mar 03 12:51:40 2010 -0500
@@ -6,12 +6,21 @@
 from jobman import DD
 
 # from pylearn codebase
+# useful in __init__(param1, param2, etc.) to save
+# values in self.param1, self.param2... just call
+# update_locals(self, locals())
 def update_locals(obj, dct):
     if 'self' in dct:
         del dct['self']
     obj.__dict__.update(dct)
 
-def produit_croise_jobs(val_dict):
+# from a dictionary of possible values for hyperparameters, e.g.
+# hp_values = {'learning_rate':[0.1, 0.01], 'num_layers': [1,2]}
+# create a list of other dictionaries representing all the possible
+# combinations, thus in this example creating:
+# [{'learning_rate': 0.1, 'num_layers': 1}, ...]
+# (similarly for combinations (0.1, 2), (0.01, 1), (0.01, 2))
+def produit_cartesien_jobs(val_dict):
     job_list = [DD()]
     all_keys = val_dict.keys()
 
@@ -27,9 +36,9 @@
 
     return job_list
 
-def test_produit_croise_jobs():
+def test_produit_cartesien_jobs():
     vals = {'a': [1,2], 'b': [3,4,5]}
-    print produit_croise_jobs(vals)
+    print produit_cartesien_jobs(vals)
 
 
 # taken from http://stackoverflow.com/questions/276052/how-to-get-current-cpu-and-ram-usage-in-python