class_docstr: A fixed size sample combiner which samples values of a specified key.
  
  This CombineFn is similar to beam.combiners.SampleCombineFn except it makes
  use of the numpy random generator which means that it accepts a seed for use
  with deterministic testing.
code: def setup(self):
      self._random_generator = np.random.default_rng(self._random_seed)
  
file_path: model-analysis/tensorflow_model_analysis/metrics/sample_metrics.py
imports: from typing import Any, List, Optional, Text, Tuple
  import apache_beam
  import numpy
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.utils import beam_util
  from tensorflow_model_analysis.utils import util
label_desc: Use image node_id 2 for calling the _FixedSizeSampleCombineFn obj's underlying member method code with example usage: obj.setup() without return types