Remove guards around b/143684500.

Several kernels have previously been disabled for std::complex due
to lack of operator support on device.  This is no longer the case,
and these kernels can now be enabled.

PiperOrigin-RevId: 363924797

keras/optimizer_v2/adadelta_test.py

@@ -22,14 +22,10 @@
 
 from absl.testing import parameterized
 import numpy as np
-from tensorflow.python.framework import test_util
 from keras import combinations
 from keras.optimizer_v2 import adadelta
 
-_DATA_TYPES = [tf.half, tf.float32, tf.float64]
-# TODO(b/143684500): Eigen to support complex sqrt
-if not test_util.IsBuiltWithNvcc():
-  _DATA_TYPES += [tf.complex64, tf.complex128]
+_DATA_TYPES = [tf.half, tf.float32, tf.float64, tf.complex64, tf.complex128]
 
 
 class AdadeltaOptimizerTest(tf.test.TestCase, parameterized.TestCase):

keras/optimizer_v2/adagrad_test.py

@@ -24,15 +24,11 @@
 
 from absl.testing import parameterized
 import numpy as np
-from tensorflow.python.framework import test_util
 from keras import combinations
 from keras.optimizer_v2 import adagrad
 from keras.optimizer_v2 import learning_rate_schedule
 
-_DATA_TYPES = [tf.half, tf.float32, tf.float64]
-# TODO(b/143684500): Eigen to support complex sqrt
-if not test_util.IsBuiltWithNvcc():
-  _DATA_TYPES += [tf.complex64, tf.complex128]
+_DATA_TYPES = [tf.half, tf.float32, tf.float64, tf.complex64, tf.complex128]
 
 
 def adagrad_update_numpy(param, accum, g_t, lr=0.001, epsilon=1e-7):

keras/optimizer_v2/rmsprop_test.py

@@ -32,10 +32,7 @@
 from keras.optimizer_v2 import learning_rate_schedule
 from keras.optimizer_v2 import rmsprop
 
-_DATA_TYPES = [tf.half, tf.float32, tf.float64]
-# TODO(b/143684500): Eigen to support complex sqrt
-if not test_util.IsBuiltWithNvcc():
-  _DATA_TYPES += [tf.complex64, tf.complex128]
+_DATA_TYPES = [tf.half, tf.float32, tf.float64, tf.complex64, tf.complex128]
 
 _TEST_PARAM_VALUES = [
     # learning_rate, rho, momentum, epsilon, centered
@@ -346,8 +343,6 @@ def testMinimizeSparseResourceVariableCentered(self):
     # TODO(tanzheny, omalleyt): Fix test in eager mode.
     with tf.Graph().as_default():
       for dtype in _DATA_TYPES:
-        if test_util.is_xla_enabled() and dtype.is_complex:
-          self.skipTest("b/143578550")
         var0 = tf.Variable([[1.0, 2.0]], dtype=dtype)
         x = tf.constant([[4.0], [5.0]], dtype=dtype)