class_docstr: Logarithmic uniform randomly sampled hyperparameter object.
class_docstr_tok: ["Logarithmic","uniform","randomly","sampled","hyperparameter","object","."]
docstr: Create a parameter to be sampled by the SearchStrategy
  
  :param str name: The parameter name. Match the Task hyperparameter name.
  :param float min_value: The minimum exponent sample to use for uniform random sampling.
  :param float max_value: The maximum exponent sample to use for uniform random sampling.
  :param float base: The base used to raise the sampled exponent.
  :param float step_size: If not ``None``, set step size (quantization) for value sampling.
  :param bool include_max_value: Range includes the ``max_value``
  
      The values are:
  
      - ``True`` - The range includes the ``max_value`` (Default)
      - ``False`` -  Does not include.
docstr_tok: ["Create","a","parameter","to","be","sampled","by","the","SearchStrategy",":","param","str","name",":","The","parameter","name",".","Match","the","Task","hyperparameter","name",".",":","param","float","min_value",":","The","minimum","exponent","sample","to","use","for","uniform","random","sampling",".",":","param","float","max_value",":","The","maximum","exponent","sample","to","use","for","uniform","random","sampling",".",":","param","float","base",":","The","base","used","to","raise","the","sampled","exponent",".",":","param","float","step_size",":","If","not","``","None","``",",","set","step","size","(","quantization",")","for","value","sampling",".",":","param","bool","include_max_value",":","Range","includes","the","``","max_value","``","The","values","are",":","-","``","True","``","-","The","range","includes","the","``","max_value","``","(","Default",")","-","``","False","``","-","Does","not","include","."]
code: def __init__(
      self,
      name,  # type: str
      min_value,  # type: float
      max_value,  # type: float
      base=10,  # type: float
      step_size=None,  # type: Optional[float]
      include_max_value=True,  # type: bool
  ):
      # type: (...) -> ()
      """
      Create a parameter to be sampled by the SearchStrategy
  
      :param str name: The parameter name. Match the Task hyperparameter name.
      :param float min_value: The minimum exponent sample to use for uniform random sampling.
      :param float max_value: The maximum exponent sample to use for uniform random sampling.
      :param float base: The base used to raise the sampled exponent.
      :param float step_size: If not ``None``, set step size (quantization) for value sampling.
      :param bool include_max_value: Range includes the ``max_value``
  
          The values are:
  
          - ``True`` - The range includes the ``max_value`` (Default)
          - ``False`` -  Does not include.
  
      """
      super().__init__(
          name,
          min_value,
          max_value,
          step_size=step_size,
          include_max_value=include_max_value,
      )
      self.base = base
  
imports: import sys
  from itertools import product
  from random import Random
  from typing import Mapping, Any, Sequence, Optional, Union
label_desc: Use image node_id 1 to create a new LogUniformParameterRange object from inherited base classes: UniformParameterRange with example: obj = LogUniformParameterRange(name, min_value, max_value, base, step_size, include_max_value)