Fixed rebasing error.

theano/sparse/basic.py

@@ -346,11 +346,10 @@ class _sparse_py_operators:
                 ret = get_item_scalar(self, args)
             else:
                 ret = get_item_2d(self, args)
+        elif isinstance(args[0], list):
+            ret = get_item_list(self, args[0])
         else:
-            if isinstance(args[0], list):
-                ret = get_item_list(self, args)
-            else:
-                ret = get_item_2d(self, args)
+            ret = get_item_2d(self, args)
         return ret
 
 
@@ -995,9 +994,8 @@ class SparseFromDense(gof.op.Op):
 csr_from_dense = SparseFromDense('csr')
 """Convert a dense matrix to a sparse csr matrix.
 
-<<<<<<< HEAD
-:param x: A dense matrix.
-=======
+"""
+
 # Indexing
 class GetItemList(gof.op.Op):
 
@@ -1012,19 +1010,16 @@ class GetItemList(gof.op.Op):
         assert x.format in ["csr", "csc"]
 
         ind = tensor.as_tensor_variable(index)
-        assert ind.ndim == 2
+        assert ind.ndim == 1
         assert 'int' in ind.dtype
 
         return gof.Apply(self, [x, ind], [x.type()])
 
     def perform(self, node, inp, (out, )):
         x = inp[0]
-        y = []
         indices = inp[1]
         assert _is_sparse(x)
-
-        for ind in indices:
-            out[0] = x[indices[0][ind]]
+        out[0] = x[indices]
 
     def __str__(self):
         return self.__class__.__name__

theano/sparse/tests/test_basic.py

@@ -2021,34 +2021,30 @@ class Test_getitem(unittest.TestCase):
         self.rng = numpy.random.RandomState(utt.fetch_seed())
 
     def test_GetItemList(self):
-        rng = numpy.random.RandomState(utt.fetch_seed())
-        a = sparse.csr_matrix()
-        b = sparse.csc_matrix()
-        y = a[[0, 1, 2, 3, 1]]
-        z = b[[0, 1, 2, 3, 1]]
 
-        fa = theano.function([a], y)
-        fb = theano.function([b], z)
+        a, A = sparse_random_inputs('csr', (4, 5))
+        b, B = sparse_random_inputs('csc', (4, 5))
+        y = a[0][[0, 1, 2, 3, 1]]
+        z = b[0][[0, 1, 2, 3, 1]]
 
-        A = rng.rand(4, 4).astype(theano.config.floatX)
+        fa = theano.function([a[0]], y)
+        fb = theano.function([b[0]], z)
 
-        t_geta = fa(numpy.asarray(A, dtype="float64")).todense()
-        t_getb = fb(numpy.asarray(A, dtype="float64")).todense()
+        t_geta = fa(A[0]).todense()
+        t_getb = fb(B[0]).todense()
 
-        s_geta = numpy.asarray(scipy.sparse.csr_matrix(A)[[0, 1, 2, 3, 1]].todense(), dtype="float64")
-        s_getb = numpy.asarray(scipy.sparse.csc_matrix(A)[[0, 1, 2, 3, 1]].todense(), dtype="float64")
+        s_geta = scipy.sparse.csr_matrix(A[0])[[0, 1, 2, 3, 1]].todense()
+        s_getb = scipy.sparse.csc_matrix(B[0])[[0, 1, 2, 3, 1]].todense()
 
         utt.assert_allclose(t_geta, s_geta)
         utt.assert_allclose(t_getb, s_getb)
 
     def test_GetItemList_wrong_index(self):
-        rng = numpy.random.RandomState(utt.fetch_seed())
-        x = sparse.csr_matrix()
-        y = x[[0, 4]]
-        f = theano.function([x], y)
+        a, A = sparse_random_inputs('csr', (4, 5))
+        y = a[0][[0, 4]]
+        f = theano.function([a[0]], y)
 
-        A = rng.rand(2, 2).astype(theano.config.floatX)
-        self.assertRaises(IndexError, f, A)
+        self.assertRaises(IndexError, f, A[0])
 
     def test_GetItem2D(self):
         sparse_formats = ('csc', 'csr')