class_docstr: An audio transform parameter with min and max value.
class_docstr_tok: ["An","audio","transform","parameter","with","min","and","max","value","."]
docstr: Initialize an AudioTransformParameter.
  
  Args:
    name: The name of the parameter. Should be the same as the name of the
        parameter passed to sox.
    min_value: The minimum value of the parameter, a float.
    max_value: The maximum value of the parameter, a float.
    scale: 'linear' or 'log', the scale with which to sample the parameter
        value.
  
  Raises:
    ValueError: If `scale` is not 'linear' or 'log'.
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code: def __init__(self, name, min_value, max_value, scale):
      """Initialize an AudioTransformParameter.
  
      Args:
        name: The name of the parameter. Should be the same as the name of the
            parameter passed to sox.
        min_value: The minimum value of the parameter, a float.
        max_value: The maximum value of the parameter, a float.
        scale: 'linear' or 'log', the scale with which to sample the parameter
            value.
  
      Raises:
        ValueError: If `scale` is not 'linear' or 'log'.
      """
      if scale not in ("linear", "log"):
          raise ValueError("invalid parameter scale: %s" % scale)
  
      self.name = name
      self.min_value = min_value
      self.max_value = max_value
      self.scale = scale
  
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 1 to create a new AudioTransformParameter object from inherited base classes: object with example: obj = AudioTransformParameter(name, min_value, max_value, scale)