Export the XLA dynamic-slice HLO as a TF op

I need this in a subsequent CL where I'll rewrite the Slice TF op to DynamicSlice in some cases.

PiperOrigin-RevId: 212715067

1 files changed, 40 insertions, 1 deletions

diff --git a/tensorflow/compiler/tests/xla_ops_test.py b/tensorflow/compiler/tests/xla_ops_test.py
index 0f3843dc1e..1e600c44e9 100644
--- a/tensorflow/compiler/tests/xla_ops_test.py
+++ b/tensorflow/compiler/tests/xla_ops_test.py
@@ -25,6 +25,7 @@ from tensorflow.compiler.tests import xla_test
 from tensorflow.compiler.tf2xla.python import xla
 from tensorflow.compiler.xla import xla_data_pb2
 from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import errors
 from tensorflow.python.framework import function
 from tensorflow.python.ops import array_ops
 from tensorflow.python.platform import googletest
@@ -34,7 +35,7 @@ class XlaOpsTest(xla_test.XLATestCase, parameterized.TestCase):
 
   def _assertOpOutputMatchesExpected(self, op, args, expected,
                                      equality_fn=None):
-    with self.cached_session() as session:
+    with self.test_session() as session:
       with self.test_scope():
         placeholders = [
             array_ops.placeholder(dtypes.as_dtype(arg.dtype), arg.shape)
@@ -296,6 +297,44 @@ class XlaOpsTest(xla_test.XLATestCase, parameterized.TestCase):
       self._assertOpOutputMatchesExpected(
           lambda x: xla.transpose(x, [1, 0]), args=(v,), expected=v.T)
 
+  def testDynamicSlice(self):
+    for dtype in self.numeric_types:
+      self._assertOpOutputMatchesExpected(
+          xla.dynamic_slice,
+          args=(np.arange(1000,
+                          dtype=np.int32).astype(dtype).reshape([10, 10, 10]),
+                np.array([5, 7, 3]), np.array([2, 3, 2])),
+          expected=np.array(
+              np.array([[[573, 574], [583, 584], [593, 594]],
+                        [[673, 674], [683, 684], [693, 694]]]),
+              dtype=dtype))
+
+  def testDynamicSliceWithIncorrectStartIndicesShape(self):
+    with self.test_session() as session:
+      with self.test_scope():
+        output = xla.dynamic_slice(
+            np.arange(1000, dtype=np.int32).reshape([10, 10, 10]),
+            np.array([5, 7]), np.array([2, 3, 4]))
+      with self.assertRaises(errors.InvalidArgumentError) as invalid_arg_error:
+        session.run(output)
+      self.assertRegexpMatches(
+          invalid_arg_error.exception.message,
+          (r'^start_indices must be a vector with length equal to input rank, '
+           r'but input rank is 3 and start_indices has shape \[2\].*'))
+
+  def testDynamicSliceWithIncorrectSizeIndicesShape(self):
+    with self.test_session() as session:
+      with self.test_scope():
+        output = xla.dynamic_slice(
+            np.arange(1000, dtype=np.int32).reshape([10, 10, 10]),
+            np.array([5, 7, 3]), np.array([2, 3]))
+      with self.assertRaises(errors.InvalidArgumentError) as invalid_arg_error:
+        session.run(output)
+      self.assertRegexpMatches(
+          invalid_arg_error.exception.message,
+          (r'^size_indices must be a vector with length equal to input rank, '
+           r'but input rank is 3 and size_indices has shape \[2\].*'))
+
 
 if __name__ == '__main__':
   googletest.main()