code: def testPartialPadding(self, graph_fn, rank):
      num_partitions = [2] * rank
      shape = [4] * rank
      value = np.arange(0, np.prod(shape)).reshape(shape)
      paddings = [2] * rank
      for dtype in self.numeric_types:
          with self.session() as sess, self.device_scope():
              validate = graph_fn(
                  sess, value, dtype, num_partitions, paddings
              )
              result = sess.run(validate)
          self.assertAllEqual(result, np.broadcast_to(True, shape))
  
imports: from typing import Any, List, Optional
  from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.client.session import Session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework.ops import control_dependencies
  from tensorflow.python.framework.ops import Tensor
  from tensorflow.python.ops import gen_tpu_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the XlaSplitConcatNDTest obj's underlying member method code with example usage: obj.testPartialPadding(graph_fn, rank) without return types