Checks that sequence_length is equal among sequence feature columns.

PiperOrigin-RevId: 188042426

2 files changed, 45 insertions, 2 deletions

diff --git a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py
index ba17b568b6..b25d7e513b 100644
--- a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py
+++ b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py
@@ -127,8 +127,9 @@ def sequence_input_layer(
                 shape=array_ops.concat([shape[:2], [num_elements]], axis=0)))
         sequence_lengths.append(sequence_length)
     fc._verify_static_batch_size_equality(output_tensors, ordered_columns)
-    # TODO(b/73160931): Verify sequence_length equality.
-    return array_ops.concat(output_tensors, -1), sequence_lengths[0]
+    fc._verify_static_batch_size_equality(sequence_lengths, ordered_columns)
+    sequence_length = _assert_all_equal_and_return(sequence_lengths)
+    return array_ops.concat(output_tensors, -1), sequence_length
 
 
 # TODO(b/73160931): Add remaining categorical columns.
@@ -312,6 +313,18 @@ def sequence_numeric_column(
       dtype=dtype)
 
 
+def _assert_all_equal_and_return(tensors, name=None):
+  """Asserts that all tensors are equal and returns the first one."""
+  with ops.name_scope(name, 'assert_all_equal', values=tensors):
+    if len(tensors) == 1:
+      return tensors[0]
+    assert_equal_ops = []
+    for t in tensors[1:]:
+      assert_equal_ops.append(check_ops.assert_equal(tensors[0], t))
+    with ops.control_dependencies(assert_equal_ops):
+      return array_ops.identity(tensors[0])
+
+
 class _SequenceDenseColumn(fc._FeatureColumn):
   """Represents dense sequence data."""
 
diff --git a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py
index 39caa602d9..5c1e76fc62 100644
--- a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py
+++ b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py
@@ -198,6 +198,36 @@ class SequenceInputLayerTest(test.TestCase):
       self.assertAllEqual(
           expected_sequence_length, sequence_length.eval(session=sess))
 
+  def test_sequence_length_not_equal(self):
+    """Tests that an error is raised when sequence lengths are not equal."""
+    # Input a with sequence_length = [2, 1]
+    sparse_input_a = sparse_tensor.SparseTensorValue(
+        indices=((0, 0), (0, 1), (1, 0)),
+        values=(0., 1., 10.),
+        dense_shape=(2, 2))
+    # Input b with sequence_length = [1, 1]
+    sparse_input_b = sparse_tensor.SparseTensorValue(
+        indices=((0, 0), (1, 0)),
+        values=(1., 10.),
+        dense_shape=(2, 2))
+    numeric_column_a = sfc.sequence_numeric_column('aaa')
+    numeric_column_b = sfc.sequence_numeric_column('bbb')
+
+    _, sequence_length = sfc.sequence_input_layer(
+        features={
+            'aaa': sparse_input_a,
+            'bbb': sparse_input_b,
+        },
+        feature_columns=[numeric_column_a, numeric_column_b])
+
+    with monitored_session.MonitoredSession() as sess:
+      with self.assertRaisesRegexp(
+          errors.InvalidArgumentError,
+          r'\[Condition x == y did not hold element-wise:\] '
+          r'\[x \(sequence_input_layer/aaa/sequence_length:0\) = \] \[2 1\] '
+          r'\[y \(sequence_input_layer/bbb/sequence_length:0\) = \] \[1 1\]'):
+        sess.run(sequence_length)
+
 
 def _assert_sparse_tensor_value(test_case, expected, actual):
   test_case.assertEqual(np.int64, np.array(actual.indices).dtype)