class_docstr: An audio transform parameter with min and max value.
class_docstr_tok: ["An","audio","transform","parameter","with","min","and","max","value","."]
docstr: Sample the parameter, returning a random value in its range.
  
  Returns:
    A value drawn uniformly at random between `min_value` and `max_value`.
docstr_tok: ["Sample","the","parameter",",","returning","a","random","value","in","its","range",".","Returns",":","A","value","drawn","uniformly","at","random","between","`","min_value","`","and","`","max_value","`","."]
code: def sample(self):
      """Sample the parameter, returning a random value in its range.
  
      Returns:
        A value drawn uniformly at random between `min_value` and `max_value`.
      """
      if self.scale == "linear":
          return random.uniform(self.min_value, self.max_value)
      else:
          log_min_value = math.log(self.min_value)
          log_max_value = math.log(self.max_value)
          return math.exp(random.uniform(log_min_value, log_max_value))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import random
  import subprocess
  import tempfile
  from magenta.contrib import training
  import sox
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the AudioTransformParameter obj's underlying member method code with example usage: obj.sample() and returns: random, math