softmax bug fix

Yusuke Sugomori · Yusuke Sugomori · commit f35193b6653f · 2013-01-12T17:31:45.000+09:00
diff --git a/DeepBeliefNets.py b/DeepBeliefNets.py
@@ -164,7 +164,7 @@ def test_dbn(pretrain_lr=0.1, pretraining_epochs=1000, k=1, \
     rng = numpy.random.RandomState(123)
 
     # construct DBN
-    dbn = DBN(input=x, label=y, n_ins=6, hidden_layer_sizes=[4, 3], n_outs=2, numpy_rng=rng)
+    dbn = DBN(input=x, label=y, n_ins=6, hidden_layer_sizes=[3, 3], n_outs=2, numpy_rng=rng)
 
     # pre-training (TrainUnsupervisedDBN)
     dbn.pretrain(lr=pretrain_lr, k=1, epochs=pretraining_epochs)
@@ -174,7 +174,10 @@ def test_dbn(pretrain_lr=0.1, pretraining_epochs=1000, k=1, \
 
 
     # test
-    x = numpy.array([1, 1, 0, 0, 0, 0])
+    x = numpy.array([[1, 1, 0, 0, 0, 0],
+                     [0, 0, 0, 1, 1, 0],
+                     [1, 1, 1, 1, 1, 0]])
+    
     print dbn.predict(x)
 
 
diff --git a/LogisticRegression.py b/LogisticRegression.py
@@ -87,7 +87,10 @@ def test_lr(learning_rate=0.01, n_epochs=200):
 
 
     # test
-    x = numpy.array([1, 1, 0, 0, 0, 0])
+    x = numpy.array([[1, 1, 0, 0, 0, 0],
+                     [0, 0, 0, 1, 1, 0],
+                     [1, 1, 1, 1, 1, 0]])
+
     print >> sys.stderr, classifier.predict(x)
 
 
diff --git a/RestrictedBoltzmannMachine.py b/RestrictedBoltzmannMachine.py
@@ -162,8 +162,8 @@ def test_rbm(learning_rate=0.1, k=1, training_epochs=1000):
 
 
     # test
-    v = numpy.array([[0, 0, 0, 1, 1, 0],
-                     [1, 1, 0, 0, 0, 0]])
+    v = numpy.array([[1, 1, 0, 0, 0, 0],
+                     [0, 0, 0, 1, 1, 0]])
 
     print rbm.reconstruct(v)
 
diff --git a/utils.py b/utils.py
@@ -17,4 +17,7 @@ def sigmoid_err_handler(type, flg):
 
 def softmax(x):
     e = numpy.exp(x - numpy.max(x))  # prevent overflow
-    return e / numpy.sum(e, axis=0)
+    if e.ndim == 1:
+        return e / numpy.sum(e, axis=0)
+    else:  
+        return e / numpy.array([numpy.sum(e, axis=1)]).T  # ndim = 2
