code: def test_boostrap_sample_combine_fn_numpy_overflow(self):
      sample_values = np.random.RandomState(seed=0).randint(0, 1e10, 20)
      metric_key = metric_types.MetricKey("metric")
      samples = [
          confidence_intervals_util.SampleMetrics(
              sample_id=poisson_bootstrap._FULL_SAMPLE_ID,
              metrics={
                  metric_key: 1,
              },
          )
      ]
      for sample_id, value in enumerate(sample_values):
          samples.append(
              confidence_intervals_util.SampleMetrics(
                  sample_id=sample_id,
                  metrics={
                      metric_key: value,
                  },
              )
          )
      with beam.Pipeline() as pipeline:
          result = (
              pipeline
              | "Create" >> beam.Create(samples, reshuffle=False)
              | "CombineSamples"
              >> beam.CombineGlobally(
                  poisson_bootstrap._BootstrapSampleCombineFn(
                      num_bootstrap_samples=20
                  )
              )
          )
  
          def check_result(got_pcoll):
              expected_pcoll = [
                  {
                      metric_key: types.ValueWithTDistribution(
                          sample_mean=5293977041.15,
                          sample_standard_deviation=3023624729.537024,
                          sample_degrees_of_freedom=19,
                          unsampled_value=1,
                      ),
                  },
              ]
              self.assertCountEqual(expected_pcoll, got_pcoll)
  
          util.assert_that(result, check_result)
  
file_path: model-analysis/tensorflow_model_analysis/evaluators/poisson_bootstrap_test.py
imports: from absl.testing import absltest
  import apache_beam
  from apache_beam.testing import util
  import numpy
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.evaluators import confidence_intervals_util
  from tensorflow_model_analysis.evaluators import poisson_bootstrap
  from tensorflow_model_analysis.metrics import binary_confusion_matrices
  from tensorflow_model_analysis.metrics import metric_types
label_desc: Use image node_id 5 for calling the PoissonBootstrapTest obj's underlying member method code with example usage: obj.test_boostrap_sample_combine_fn_numpy_overflow() without return types