Fix negative axis issue with ragged tensor and reduce_sum

tensorflow/python/ops/ragged/ragged_math_ops.py

@@ -461,6 +461,12 @@ def _ragged_reduce_aggregate(reduce_op,
       elif len(axis) == 1:
         axis = axis[0]
       else:
+        # When reducing multiple axes, as we reduce one at a time (see below),
+        # the negative axis has to be converted to positive at the first run
+        # as the sort with negative axis will have different orders.
+        # See GitHub issue 27497.
+        axis = [ragged_util.get_positive_axis(
+            a, rt_input.shape.ndims) for a in axis]
         # When reducing multiple axes, just reduce one at a time.  This is less
         # efficient, and only works for associative ops.  (In particular, it
         # does not work for reduce_mean.)  However, reducing multiple axes at

tensorflow/python/ops/ragged/ragged_reduce_op_test.py

@@ -304,6 +304,18 @@ class RaggedReduceOpsTest(ragged_test_util.RaggedTensorTestCase,
           rt_input=[[[1, 2], [3, 4, 5]], [[6, 7], [8]], [[9]]],
           axis=2,
           expected=[[mean(1, 2), mean(3, 4, 5)], [mean(6, 7), 8], [9]]),
+
+      # Test case for GitHub issue 27497, multiple negative axes.
+      dict(
+          ragged_reduce_op=ragged_math_ops.reduce_sum,
+          rt_input=[[[1, 2], [], [3, 4, 5]], [[6, 7], [], [8]], [], [[9]]],
+          axis=[-2, -1],
+          expected=[1 + 2 + 3 + 4 + 5, 6 + 7 + 8, 0, 9]),
+      dict(
+          ragged_reduce_op=ragged_math_ops.reduce_sum,
+          rt_input=[[[1, 2], [], [3, 4, 5]], [[6, 7], [], [8]], [], [[9]]],
+          axis=[-3, -2, -1],
+          expected=sum([1, 2, 3, 4, 5, 6, 7, 8, 9])),
   )
   def testReduce(self, ragged_reduce_op, rt_input, axis, expected):
     rt_input = ragged_factory_ops.constant(rt_input)