code: def testMapAndBatchTypes(self, element, dtype):
      def gen():
          yield element
  
      dataset = (
          dataset_ops.Dataset.from_generator(gen, dtype)
          .repeat(100)
          .apply(batching.map_and_batch(lambda x: x, batch_size=10))
      )
  
      get_next = self.getNext(dataset)
      for _ in range(10):
          self.assertAllEqual(
              [element for _ in range(10)], self.evaluate(get_next())
          )
  
imports: import math
  from absl.testing import parameterized
  import numpy
  from tensorflow.python import pywrap_sanitizers
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.checkpoint import checkpoint_management
  from tensorflow.python.data.experimental.ops import batching
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.eager import context
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 11 for calling the MapAndBatchTest obj's underlying member method code with example usage: obj.testMapAndBatchTypes(element, dtype) without return types