Fix the grad of theano.sparse.sandbox.sp.row_scale and test it.

NEWS.txt

@@ -2,6 +2,10 @@
 
 Updates in the Trunk since the last release:
 
+Sparse Sandbox bugfix
+ * Fix the grad of theano.sparse.sandbox.sp.row_scale. It didn't
+   returned the right number of element. (Frederic B.)
+
 Documentation
  * Added in the tutorial documentation on how to extend Theano.
    This explains how to make a Theano Op from a Python function.
@@ -36,7 +40,6 @@ New Features
    contains dimensions with bad value like 0. (Frédéric B. reported by Ian G.)
 
 Sparse
-
  * Implement theano.sparse.mul(sparse1, sparse2) when both input don't
    have the same sparsity pattern. (Frederic B.)
 

theano/sparse/sandbox/sp.py

@@ -263,7 +263,7 @@ class RowScaleCSC(Op):
         z[0] = scipy_sparse.csc_matrix((y_data, indices, indptr), (M, N))
 
     def grad(self, (x, s), (gz,)):
-        return [row_scale(gz, s), sp_sum(x * gz, axis=0)]
+        return [row_scale(gz, s), sp_sum(x * gz, axis=1)]
 
 
 def col_scale(x, s):

theano/sparse/sandbox/test_sp.py

@@ -494,19 +494,17 @@ def test_diag_grad():
     utt.verify_grad(d, [diag_mat],
             mode=theano.Mode(linker='py', optimizer='fast_compile'))
 
+
 def test_row_scale():
     x = theano.sparse.csc_dmatrix()
     s = theano.tensor.dvector()
 
-    def d(x,s):
-        return sp.sp_sum(sp.row_scale(x, s), sparse_grad=True)
-
     rng = numpy.random.RandomState(8723)
     R = 5
     C = 8
 
-    x_val_dense = numpy.zeros((R, C),dtype='d')
-    for idx in [(0,0), (4, 1), (2,1), (3, 3), (4, 4), (3, 7), (2, 7)]:
+    x_val_dense = numpy.zeros((R, C), dtype='d')
+    for idx in [(0, 0), (4, 1), (2, 1), (3, 3), (4, 4), (3, 7), (2, 7)]:
         x_val_dense.__setitem__(idx, rng.randn())
     x_val = scipy.sparse.csc_matrix(x_val_dense)
 
@@ -519,11 +517,8 @@ def test_row_scale():
 
     assert numpy.all(f(x_val, s_val).toarray() == (x_val_dense.T * s_val).T)
 
-    if 0:
-        tensor.verify_grad(None, d, [x_val, s_val],
-                mode=theano.Mode(linker='py', optimizer='fast_compile'))
-    else:
-        print >> sys.stderr, "WARNING: skipping gradient test because verify_grad doesn't support sparse arguments"
+    verify_grad_sparse(sp.row_scale, [x_val, s_val], structured=False)
+
 
 def test_col_scale():
     x = theano.sparse.csc_dmatrix()