Unit tests for InversePermutation and ReorderRowElements Ops.

theano/tensor/tests/test_basic.py

@@ -1784,12 +1784,104 @@ def test_flatten_outdim_invalid():
         assert False
     except ValueError:
         pass
-        
+
 # TODO: write test case for Tile Op
 def test_tile():
     print >> sys.stderr, "WARNING: No testcase for Tile"
     pass 
 
+class TestInversePermutation(unittest.TestCase):
+    def setUp(self):
+        utt.seed_rng()
+
+    def test_dim1(self):
+        p = ivector()
+        inv = inverse_permutation(p)
+        f_inverse = function([p], inv)
+
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        p_val = rng.permutation(10)
+        inv_val = f_inverse(p_val)
+
+        assert numpy.all(f_inverse(inv_val) == p_val)
+        assert numpy.all(p_val[inv_val] == numpy.arange(10))
+        assert numpy.all(inv_val[p_val] == numpy.arange(10))
+
+    def test_dim2(self):
+        p = imatrix()
+        inv = inverse_permutation(p)
+        f_inverse = function([p], inv)
+
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        p_val = numpy.asarray([rng.permutation(10) for i in range(7)])
+        inv_val = f_inverse(p_val)
+
+        assert numpy.all(f_inverse(inv_val) == p_val)
+        for p_row, i_row in zip(p_val, inv_val):
+            assert numpy.all(p_row[i_row] == numpy.arange(10))
+            assert numpy.all(i_row[p_row] == numpy.arange(10))
+
+
+class TestReorderRowElements(unittest.TestCase):
+    def setUp(self):
+        utt.seed_rng()
+
+    def test_1_1(self):
+        input = vector()
+        p = ivector()
+        out = reorder_row_elements(input, p)
+        reorder = function([input, p], out)
+
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        input_val = rng.uniform(size=(5,))
+        p_val = rng.permutation(5)
+        out_val = reorder(input_val, p_val)
+
+        out_bis = input_val[p_val]
+        assert numpy.all(out_val == out_bis)
+
+        # Verify gradient
+        def reorder_fixed(s_input):
+            return reorder_row_elements(s_input, p_val)
+        utt.verify_grad(reorder_fixed, [input_val])
+
+    def test_2_1(self):
+        input = matrix()
+        p = ivector()
+        out = reorder_row_elements(input, p)
+        reorder = function([input, p], out)
+
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        input_val = rng.uniform(size=(3,5))
+        p_val = rng.permutation(5)
+        out_val = reorder(input_val, p_val)
+
+        out_bis = numpy.asarray([row[p_val] for row in input_val])
+        assert numpy.all(out_val == out_bis)
+
+        # Verify gradient
+        def reorder_fixed(s_input):
+            return reorder_row_elements(s_input, p_val)
+        utt.verify_grad(reorder_fixed, [input_val])
+
+    def test_2_2(self):
+        input = matrix()
+        p = imatrix()
+        out = reorder_row_elements(input, p)
+        reorder = function([input, p], out)
+
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        input_val = rng.uniform(size=(3,5))
+        p_val = numpy.asarray([rng.permutation(5) for i in range(3)])
+        out_val = reorder(input_val, p_val)
+
+        out_bis = numpy.asarray([i_row[p_row] for i_row, p_row in zip(input_val, p_val)])
+        assert numpy.all(out_val == out_bis)
+
+        # Verify gradient
+        def reorder_fixed(s_input):
+            return reorder_row_elements(s_input, p_val)
+        utt.verify_grad(reorder_fixed, [input_val])
 
 class test_tensordot(unittest.TestCase):
     def setUp(self):