# HG changeset patch
# User bergstra@ip05.m
# Date 1243892696 14400
# Node ID 4d22396678e6003c295d2c12390e3398727f73b0
# Parent  504ce30bbd2a34c248f607dbf037cdbe20d95790
typos in parameter names

diff -r 504ce30bbd2a -r 4d22396678e6 pylearn/algorithms/sgd.py
--- a/pylearn/algorithms/sgd.py	Mon Jun 01 00:22:35 2009 -0400
+++ b/pylearn/algorithms/sgd.py	Mon Jun 01 17:44:56 2009 -0400
@@ -56,7 +56,7 @@
     
     :returns: standard minimizer constructor f(args, cost, params, gradient=None)
     """
-    def f(args, cost, params, gradient=None, updates=None, auxout=None):
-        return StochasticGradientDescent(args, cost, params, gradient, stepsize,
+    def f(args, cost, params, gradients=None, updates=None, auxout=None):
+        return StochasticGradientDescent(args, cost, params, gradients=gradients, stepsize=stepsize,
                 updates=updates, auxout=auxout)
     return f
diff -r 504ce30bbd2a -r 4d22396678e6 pylearn/algorithms/stopper.py
--- a/pylearn/algorithms/stopper.py	Mon Jun 01 00:22:35 2009 -0400
+++ b/pylearn/algorithms/stopper.py	Mon Jun 01 17:44:56 2009 -0400
@@ -100,7 +100,7 @@
 
         starting = self.iter < self.initial_wait
         waiting = self.iter < (self.patience * self.best_iter)
-        times_up = (time.time() - self.start_time) > self.hard_limit_second if self.hard_limit_second != None else False
+        times_up = (time.time() - self.start_time) > self.hard_limit_seconds if self.hard_limit_seconds != None else False
         if (starting or waiting) and not times_up:
             # continue to iterate
             self.iter += 1