class_docstr: Deterministic value sampler.
  
  For a value it returns whether this value should be kept. The keeping
  decision is deterministic for a fixed value. For a randomly chosen value the
  decision to keep happens with probability sampling_rate.
code: def __init__(self, sampling_rate: float):
      self._sample_bound = int(round(2**64 * sampling_rate))
  
imports: import numpy
  import hashlib
label_desc: Use image node_id 1 to create a new ValueSampler object  with example: obj = ValueSampler(sampling_rate)