class_docstr: Map X to [0, 1]^d for RangeParameter of type float and not log scale.
  
  Uses bounds l <= x <= u, sets x_tilde_i = (x_i - l_i) / (u_i - l_i).
  Constraints wTx <= b are converted to gTx_tilde <= h, where
  g_i = w_i (u_i - l_i) and h = b - wTl.
  
  Transform is done in-place.
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docstr: Normalize the given value - bounds pair to
  [self.target_lb, self.target_lb + self.target_range].
docstr_tok: ["Normalize","the","given","value","-","bounds","pair","to","[","self.target_lb",",","self.target_lb","+","self.target_range","]","."]
code: def _normalize_value(
      self, value: float, bounds: Tuple[float, float]
  ) -> float:
      """Normalize the given value - bounds pair to
      [self.target_lb, self.target_lb + self.target_range].
      """
      lower, upper = bounds
      return (value - lower) / (
          upper - lower
      ) * self.target_range + self.target_lb
  
imports: from typing import Dict, List, Optional, Tuple, TYPE_CHECKING
  import numpy
  from ax.core.observation import Observation, ObservationFeatures
  from ax.core.parameter import ParameterType, RangeParameter
  from ax.core.parameter_constraint import ParameterConstraint
  from ax.core.parameter_distribution import ParameterDistribution
  from ax.core.search_space import RobustSearchSpace, SearchSpace
  from ax.exceptions.core import UnsupportedError, UserInputError
  from ax.modelbridge.transforms.base import Transform
  from ax.models.types import TConfig
label_desc: Use image node_id 8 for calling the UnitX obj's underlying member method code with example usage: obj._normalize_value(value, bounds) and returns: unknown