code: def testGPUTooManyParts(self):
      # This test only makes sense on the GPU. There we do not check
      # for errors. In this case, we should discard all but the first
      # num_partitions indices.
      if not test.is_gpu_available():
          return
  
      data_list = [1, 2, 3, 4, 5, 6]
      indices_list = [6, 5, 4, 3, 1, 0]
      with self.session():
          data = constant_op.constant(data_list, dtype=dtypes.float32)
          indices = constant_op.constant(
              indices_list, dtype=dtypes.int32
          )
          partitions = data_flow_ops.dynamic_partition(
              data, indices, num_partitions=2
          )
          partition_vals = self.evaluate(partitions)
  
      self.assertEqual(2, len(partition_vals))
      self.assertAllEqual([6], partition_vals[0])
      self.assertAllEqual([5], partition_vals[1])
  
imports: import unittest
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import config
  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.ops import array_ops
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.ops import gradients_impl
  import tensorflow.python.ops.data_flow_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 11 for calling the DynamicPartitionTest obj's underlying member method code with example usage: obj.testGPUTooManyParts() without return types