code: def unif(step_size, elow=0.85, ehigh=1.15):
      return np.random.uniform(elow, ehigh) * step_size
  
file_path: pymc/pymc/step_methods/hmc/hmc.py
imports: from __future__ import annotations
  from typing import Any
  import numpy
  from pymc.stats.convergence import SamplerWarning
  from pymc.step_methods.compound import Competence
  from pymc.step_methods.hmc.base_hmc import BaseHMC, DivergenceInfo, HMCStepData
  from pymc.step_methods.hmc.integration import IntegrationError, State
  from pymc.vartypes import discrete_types
label_desc: Use image node_id 1 for calling a global function with example usage: unif(step_size, elow, ehigh) and returns: unknown