* added 3D kernels to test case + removed a few debug prints on ConvOp

theano/sandbox/conv.py

@@ -120,7 +120,6 @@ class ConvOp(Op):
         mode = self.out_mode
         if inputs.ndim == 3:
             inputs = tensor.shape_padleft(inputs,1)
-        print 'self.imshp = ', self.imshp
 
         img = tensor.DimShuffle(inputs.broadcastable, (1,0,2,3))(inputs)
         imshp = N.hstack((self.bsize, self.imshp[1:]))
@@ -132,8 +131,6 @@ class ConvOp(Op):
 
         kshp  = self.outshp[::-1]
 
-        print kshp, imshp
-
         dw = ConvOp(imshp, kshp, nkern, bsize, 1,1, output_mode=mode)(img,filters)
         dw = tensor.DimShuffle(dw.broadcastable, (1,0,2,3))(dw)
         dw = dw[:,:,::-1,::-1]
@@ -425,10 +422,6 @@ def convolve2(kerns, kshp, nkern, images, imshp, bsize, step=(1,1),
     kernrshp   = tensor.as_tensor([nkern, nvis_dim] + list(kshp))
     kerntensor = tensor.reshape(kerns, kernrshp)
    
-    print '***** convolve2 *****'
-    print 'imrshp = ', imrshp
-    print 'kernrshp = ', kernrshp
-
     convop = ConvOp(imshp, kshp, nkern, bsize, 1, 1, output_mode=mode)
     convout = convop(imtensor, kerntensor)
    

theano/sandbox/test_conv.py

@@ -317,7 +317,10 @@ class TestConvOp(unittest.TestCase):
                     print 'imgvals.shape = ', imgvals.shape
                     imgvals = imgvals.reshape(bsize,-1)
 
-                    kernvals = N.random.rand(nkern,visdim,kshp[0],kshp[1])
+                    if visdim == 1: 
+                        kernvals = N.random.rand(nkern,kshp[0],kshp[1])
+                    else:
+                        kernvals = N.random.rand(nkern,visdim,kshp[0],kshp[1])
                     print 'kernvals.shape = ', kernvals.shape
                     kernvals = kernvals.reshape(nkern,-1)