class_docstr: Chooses DPStrategy based on DP budget, computation sensitivites, etc
  
  It chooses noise_kind to minimize the noise std deviation.
  For non-public partitions it chooses partition selection strategy to
  minimize threshold. For more details see docstring to
  select_partition_selection_strategy().
code: def _get_laplace_std(
      self, epsilon: float, sensitivities: dp_computations.Sensitivities
  ) -> float:
      return dp_computations.LaplaceMechanism.create_from_epsilon(
          epsilon, sensitivities.l1
      ).std
  
imports: from dataclasses import dataclass
  from typing import Optional
  import pipeline_dp
  from pipeline_dp import aggregate_params
  from pipeline_dp import dp_computations
  from pipeline_dp import input_validators
label_desc: Use image node_id 10 for calling the DPStrategySelector obj's underlying member method code with example usage: obj._get_laplace_std(epsilon, sensitivities) and returns: dp_computations