diff options
Diffstat (limited to 'tensorflow/python/kernel_tests/segment_reduction_ops_test.py')
-rw-r--r-- | tensorflow/python/kernel_tests/segment_reduction_ops_test.py | 29 |
1 files changed, 1 insertions, 28 deletions
diff --git a/tensorflow/python/kernel_tests/segment_reduction_ops_test.py b/tensorflow/python/kernel_tests/segment_reduction_ops_test.py index 3a02f24902..516a9d000e 100644 --- a/tensorflow/python/kernel_tests/segment_reduction_ops_test.py +++ b/tensorflow/python/kernel_tests/segment_reduction_ops_test.py @@ -323,9 +323,8 @@ class UnsortedSegmentSumTest(SegmentReductionHelper): def testBadIndices(self): # Note: GPU kernel does not return the out-of-range error needed for this # test, so this test is marked as cpu-only. - # Note: With PR #13055 a negative index will be ignored silently. with self.test_session(use_gpu=False): - for bad in [[2]], [[7]]: + for bad in [[-1]], [[7]]: unsorted = math_ops.unsorted_segment_sum([[17]], bad, num_segments=2) with self.assertRaisesOpError( r"segment_ids\[0,0\] = %d is out of range \[0, 2\)" % bad[0][0]): @@ -361,32 +360,6 @@ class UnsortedSegmentSumTest(SegmentReductionHelper): x_init_value=np_x.astype(np.double), delta=1) self.assertAllClose(jacob_t, jacob_n) - def testDropNegatives(self): - # Note: the test is done by replacing segment_ids with 8 to -1 - # for index and replace values generated by numpy with 0. - dtypes = [ - dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int64, - dtypes_lib.int32, dtypes_lib.complex64, dtypes_lib.complex128 - ] - indices_flat = np.array([0, 4, 0, 8, 3, 8, 4, 7, 7, 3]) - num_segments = 12 - for indices in indices_flat, indices_flat.reshape(5, 2): - shape = indices.shape + (2,) - for dtype in dtypes: - with self.test_session(use_gpu=True): - tf_x, np_x = self._input(shape, dtype=dtype) - np_ans = self._segmentReduce( - indices, np_x, np.add, op2=None, num_out_rows=num_segments) - # Replace np_ans[8] with 0 for the value - np_ans[8:] = 0 - # Replace 8 with -1 in indices - np.place(indices, indices==8, [-1]) - s = math_ops.unsorted_segment_sum( - data=tf_x, segment_ids=indices, num_segments=num_segments) - tf_ans = s.eval() - self.assertAllClose(np_ans, tf_ans) - self.assertShapeEqual(np_ans, s) - class SparseSegmentReductionHelper(SegmentReductionHelper): |