message: Update cross_device_utils_test to not rely on Keras.
  Remove the usage of keras.Input and replace it with tf placeholder, which is used by keras.Input under the hood.
  Also remove the duplicated test.
diff: @@ -29,7 +29,6 @@ from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  -from tensorflow.python.keras.engine import input_layer
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  @@ -184,23 +183,10 @@ class PackBySizeTest(test.TestCase):
  self.assertShape(packs[0][1], [2])
  def testUnknownShape(self):
  - per_replica_values = [
  - value_lib.PerReplica([
  - array_ops.ones([10, 10], dtype=dtypes.float32),
  - array_ops.ones([10, 10], dtype=dtypes.float32),
  - ]),
  - value_lib.PerReplica([
  - array_ops.ones([10, 10], dtype=dtypes.float32),
  - input_layer.Input(
  - shape=(10), batch_size=None, dtype=dtypes.float32),
  - ]),
  - ]
  - packs = cross_device_utils.pack_by_size(
  - per_replica_values, bytes_per_pack=1)
  - self.assertLen(packs, 1)
  - self.assertEqual(packs[0], per_replica_values)
  + def create_placeholder(shape, dtype):
  + with ops.Graph().as_default():
  + return array_ops.placeholder(dtype=dtype, shape=shape)
  - def testInconsistentShape(self):
  per_replica_values = [
  value_lib.PerReplica([
  array_ops.ones([10, 10], dtype=dtypes.float32),
  @@ -208,8 +194,7 @@ class PackBySizeTest(test.TestCase):
  ]),
  value_lib.PerReplica([
  array_ops.ones([10, 10], dtype=dtypes.float32),
  - input_layer.Input(
  - shape=(10), batch_size=None, dtype=dtypes.float32),
  + create_placeholder([None, 10], dtype=dtypes.float32),
  ]),
  ]
  packs = cross_device_utils.pack_by_size(
  