Updates Theano downsample.max_pool_2d to pool.pool_2d

cmds/run_Extract_Feats.py

@@ -52,7 +52,7 @@
     nnet_cfg = arguments['nnet_cfg']
     output_file = arguments['output_file']
     layer_index = int(arguments['layer_index'])
-    batch_size = float(arguments['batch_size'])
+    batch_size = int(arguments['batch_size'])
     argmax = arguments.has_key('argmax') and string2bool(arguments['argmax'])
 
     # load network configuration and set up the model

layers/conv.py

@@ -23,7 +23,7 @@
 
 import theano
 import theano.tensor as T
-from theano.tensor.signal import downsample
+from theano.tensor.signal import pool
 from theano.tensor.nnet import conv
 
 class ConvLayer(object):
@@ -174,7 +174,7 @@ def __init__(self, numpy_rng=None, input = None, filter_shape=(2, 1, 5, 5),
 
             y_out = activation(conv_out + self.b.dimshuffle('x', 0, 'x', 'x'))
             # downsample each feature map individually, using maxpooling
-            self.output = downsample.max_pool_2d(input=y_out,
+            self.output = pool.pool_2d(input=y_out,
                                              ds=poolsize, ignore_border=True)
         if self.flatten:
             self.output = self.output.flatten(2)

models/cnn.py

@@ -25,7 +25,7 @@
 
 import theano
 import theano.tensor as T
-from theano.tensor.signal import downsample
+from theano.tensor.signal import pool
 from theano.tensor.nnet import conv
 
 from layers.logistic_sgd import LogisticRegression