class_docstr: Implement a gradient descent algorithm.
docstr: Declare `learning_rate` as a hyperparameter of this algorithm.
code: def __init__(self, space, learning_rate=1.0, dx_tolerance=1e-5):
      """Declare `learning_rate` as a hyperparameter of this algorithm."""
      super().__init__(
          space, learning_rate=learning_rate, dx_tolerance=dx_tolerance
      )
      self.has_observed_once = False
      self.current_point = None
      self.gradient = numpy.array([numpy.inf])
  
file_path: orion/tests/functional/gradient_descent_algo/src/orion/algo/gradient_descent.py
imports: import numpy
  from orion.algo.base import BaseAlgorithm
  from orion.core.utils import format_trials
label_desc: Use image node_id 1 to create a new Gradient_Descent object from inherited base classes: BaseAlgorithm with example: obj = Gradient_Descent(space, learning_rate, dx_tolerance)