Modified theano.prod gradient based on James' suggestion

theano/tensor/elemwise.py

@@ -1173,20 +1173,25 @@ class Prod(CAReduce):
                 new_dims.append(i)
                 i += 1
 
+        p_gz = theano.tensor.mul(prod_out, gz)
+        p_gz = DimShuffle(p_gz.type.broadcastable, new_dims)(p_gz)
+
+        return [Elemwise(scalar.true_div)(p_gz, x)]
+
         # fill a matrix with the same shape as x by broadcasting
         # values taken from gz, which has the same shape as the output
         # of prod().
-        gz_filled_x = Elemwise(scalar.second)(x, 
-                        DimShuffle(gz.type.broadcastable, new_dims)(gz))
+        #gz_filled_x = Elemwise(scalar.second)(x, 
+        #                DimShuffle(gz.type.broadcastable, new_dims)(gz))
 
         # do the same with the output of prod, by broadcasting along
         # axises where the product was taken
-        prod_out_filled_x = Elemwise(scalar.second)(x, 
-                        DimShuffle(prod_out.type.broadcastable,
-                                    new_dims)(prod_out))
+        #prod_out_filled_x = Elemwise(scalar.second)(x, 
+        #                DimShuffle(prod_out.type.broadcastable,
+        #                            new_dims)(prod_out))
 
-        return [theano.tensor.mul(gz_filled_x,
-                    theano.tensor.true_div(prod_out_filled_x, x))]
+        #return [theano.tensor.mul(gz_filled_x,
+        #            theano.tensor.true_div(prod_out_filled_x, x))]
         #else:
         #    raise NotImplementedError('Will be implemented shortly')
 

theano/tensor/tests/test_elemwise.py

@@ -301,5 +301,6 @@ class test_Prod(unittest.TestCase):
 if __name__ == '__main__':
     unittest.main()
     #suite = unittest.TestSuite([test_Prod('test_prod_grad')])
+    #suite.addTest(test_Prod('test_verify_grad'))
     #unittest.TextTestRunner().run(suite)