Enable TridiagonalSolve and XlaSort op for fallback path lowering

Also, enable compiler/tests for reduce_ops_test

PiperOrigin-RevId: 338778787
Change-Id: I7db2ff2281f6404884fcf12204042a70b97a6782

tensorflow/compiler/mlir/xla/transforms/legalize_tf_with_tf2xla.cc

@@ -232,6 +232,7 @@ bool IsOpAllowedTf2XlaFallback(Operation* op) {
     TypeID::get<TF::TensorScatterSubOp>(),
     TypeID::get<TF::TPUEmbeddingActivationsOp>(),
     TypeID::get<TF::TransposeOp>(),
+    TypeID::get<TF::TridiagonalSolveOp>(),
     TypeID::get<TF::TruncateDivOp>(),
     TypeID::get<TF::TruncatedNormalOp>(),
     TypeID::get<TF::TruncateModOp>(),
@@ -247,7 +248,8 @@ bool IsOpAllowedTf2XlaFallback(Operation* op) {
     TypeID::get<TF::XlaKeyValueSortOp>(),
     TypeID::get<TF::XlaPadOp>(),
     TypeID::get<TF::Xlog1pyOp>(),
-    TypeID::get<TF::XlogyOp>()
+    TypeID::get<TF::XlogyOp>(),
+    TypeID::get<TF::XlaSortOp>()
   };
   // clang-format on
 

tensorflow/compiler/tests/BUILD

@@ -1087,6 +1087,7 @@ tf_xla_py_test(
     name = "reduce_ops_test",
     size = "medium",
     srcs = ["reduce_ops_test.py"],
+    enable_mlir_bridge = True,
     python_version = "PY3",
     shard_count = 5,
     tags = [
@@ -1546,6 +1547,7 @@ tf_xla_py_test(
     name = "sort_ops_test",
     size = "medium",
     srcs = ["sort_ops_test.py"],
+    enable_mlir_bridge = True,
     python_version = "PY3",
     shard_count = 1,
     # Times out in fastbuild mode.
@@ -1889,6 +1891,7 @@ tf_xla_py_test(
         "cpu",
         "gpu",
     ],
+    enable_mlir_bridge = True,
     python_version = "PY3",
     tags = [
         "no_pip",  # TODO(b/149738646): fix pip install so these tests run on kokoro pip

tensorflow/compiler/tests/reduce_ops_test.py

@@ -27,6 +27,7 @@ import numpy as np
 from tensorflow.compiler.tests import xla_test
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.platform import googletest
@@ -63,13 +64,16 @@ class ReduceOpsTest(xla_test.XLATestCase, parameterized.TestCase):
         self.assertAllClose(
             result, np_reduce_fn(test_input, axis=1), rtol=rtol, atol=atol)
 
-        with self.assertRaisesWithPredicateMatch(
+        # MLIR bridge doesn't return the same error so it can't be matched
-            errors_impl.InvalidArgumentError, 'Invalid reduction dim'):
+        # directly.
-          sess.run(out, {a: test_input, index: [-33]})
+        if not test_util.is_mlir_bridge_enabled():
+          with self.assertRaisesWithPredicateMatch(
+              errors_impl.InvalidArgumentError, 'Invalid reduction dim'):
+            sess.run(out, {a: test_input, index: [-33]})
 
-        with self.assertRaisesWithPredicateMatch(
+          with self.assertRaisesWithPredicateMatch(
-            errors_impl.InvalidArgumentError, 'Invalid reduction dim'):
+              errors_impl.InvalidArgumentError, 'Invalid reduction dim'):
-          sess.run(out, {a: test_input, index: [2]})
+            sess.run(out, {a: test_input, index: [2]})
 
   REAL_DATA = [
       np.zeros(shape=(2, 0)),
@@ -168,6 +172,7 @@ class ReduceOpsTest(xla_test.XLATestCase, parameterized.TestCase):
     self._testReduction(math_ops.reduce_any, np.any, np.bool, self.BOOL_DATA,
                         index_dtype)
 
+  @test_util.disable_mlir_bridge('Error messages differ')
   def testReduceSumWithDuplicateAxes(self, index_dtype):
     with self.session() as sess:
       with self.test_scope():

tensorflow/compiler/tests/sort_ops_test.py

@@ -24,6 +24,7 @@ from tensorflow.compiler.tests import xla_test
 from tensorflow.compiler.tf2xla.python import xla
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import nn_ops
 from tensorflow.python.platform import test
@@ -127,6 +128,7 @@ class XlaSortOpTest(xla_test.XLATestCase):
               topk, [x.astype(dtype)],
               expected=[expected.astype(dtype), indices])
 
+  @test_util.disable_mlir_bridge("Support compare type in HLO Compare Op")
   def testTopKZeros(self):
     """Tests that positive and negative zeros sort correctly."""
     supported_types = set([dtypes.bfloat16.as_numpy_dtype, np.float32])

tensorflow/compiler/tests/tridiagonal_solve_ops_test.py

@@ -24,6 +24,7 @@ from tensorflow.compiler.tests import xla_test
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import errors_impl
+from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import gradients as gradient_ops
 from tensorflow.python.ops import math_ops
@@ -211,6 +212,7 @@ class TridiagonalSolveOpsTest(xla_test.XLATestCase):
 
   # test2x2NotInvertible is skipped as runtime error not raised for now.
 
+  @test_util.disable_mlir_bridge("Error messages differ")
   def testPartialPivotingRaises(self):
     np.random.seed(0)
     batch_size = 8