From efd6d49fa1b6ea9dda6ccfa13c4d45c14d558d0a Mon Sep 17 00:00:00 2001
From: Matt Graham <matthew.m.graham@gmail.com>
Date: Tue, 1 Dec 2015 15:04:50 +0000
Subject: [PATCH] Making schedulers get_rate interface consistent with use in
 optimisers (i.e. gets passed accuracy not error rate).

---
 mlp/schedulers.py | 32 +++++++++++++++++---------------
 1 file changed, 17 insertions(+), 15 deletions(-)

diff --git a/mlp/schedulers.py b/mlp/schedulers.py
index 914ea29..6ae9597 100644
--- a/mlp/schedulers.py
+++ b/mlp/schedulers.py
@@ -15,7 +15,7 @@ class LearningRateScheduler(object):
     def get_rate(self):
         raise NotImplementedError()
 
-    def get_next_rate(self, current_error=None):
+    def get_next_rate(self, current_accuracy=None):
         self.epoch += 1
 
 
@@ -35,8 +35,8 @@ class LearningRateList(LearningRateScheduler):
             return self.lr_list[self.epoch]
         return 0.0
     
-    def get_next_rate(self, current_error=None):
-        super(LearningRateList, self).get_next_rate(current_error=None)
+    def get_next_rate(self, current_accuracy=None):
+        super(LearningRateList, self).get_next_rate(current_accuracy=None)
         return self.get_rate()
 
 
@@ -53,18 +53,21 @@ class LearningRateFixed(LearningRateList):
             return self.lr_list[0]
         return 0.0
 
-    def get_next_rate(self, current_error=None):
-        super(LearningRateFixed, self).get_next_rate(current_error=None)
+    def get_next_rate(self, current_accuracy=None):
+        super(LearningRateFixed, self).get_next_rate(current_accuracy=None)
         return self.get_rate()
 
 
 class LearningRateNewBob(LearningRateScheduler):
     """
-    Exponential learning rate schema
+    newbob learning rate schedule.
+    
+    Fixed learning rate until validation set stops improving then exponential
+    decay.
     """
     
-    def __init__(self, start_rate, scale_by=.5, max_epochs=99, \
-                 min_derror_ramp_start=.5, min_derror_stop=.5, init_error=100.0, \
+    def __init__(self, start_rate, scale_by=.5, max_epochs=99,
+                 min_derror_ramp_start=.5, min_derror_stop=.5, init_error=100.0,
                  patience=0, zero_rate=None, ramping=False):
         """
         :type start_rate: float
@@ -84,8 +87,6 @@ class LearningRateNewBob(LearningRateScheduler):
         
         :type init_error: float
         :param init_error: 
-                       # deltas2 below are just deltas returned by linear Linear,bprop transform
-        # and are exactly the same as
         """
         self.start_rate = start_rate
         self.init_error = init_error
@@ -115,13 +116,14 @@ class LearningRateNewBob(LearningRateScheduler):
             return self.zero_rate
         return self.rate  
     
-    def get_next_rate(self, current_error):
+    def get_next_rate(self, current_accuracy):
         """
-        :type current_error: float
-        :param current_error: percentage error 
+        :type current_accuracy: float
+        :param current_accuracy: current proportion correctly classified
         
         """
         
+        current_error = 1. - current_accuracy
         diff_error = 0.0
         
         if ( (self.max_epochs > 10000) or (self.epoch >= self.max_epochs) ):
@@ -166,5 +168,5 @@ class DropoutFixed(LearningRateList):
     def get_rate(self):
         return self.lr_list[0]
 
-    def get_next_rate(self, current_error=None):
-        return self.get_rate()
\ No newline at end of file
+    def get_next_rate(self, current_accuracy=None):
+        return self.get_rate()