class_docstr: Grid Search algorithm
  
  Parameters
  ----------
  n_values: int or dict
      Number of trials for each dimensions, or dictionary specifying number of trials for each
      dimension independently (name, n_values). For categorical dimensions, n_values will not be
      used, and all categories will be used to build the grid.
docstr: Return True when all grid has been covered.
docstr_tok: ["Return","True","when","all","grid","has","been","covered","."]
code: def is_done(self):
      """Return True when all grid has been covered."""
      # NOTE: GridSearch doesn't care about the space cardinality, it can just check if the grid
      # has been completely explored.
      return (
          self.has_completed_max_trials
          or self.grid is not None
          and self.n_suggested >= len(self.grid)
      )
  
imports: from __future__ import annotations
  import itertools
  import logging
  import numpy
  from orion.algo.base import BaseAlgorithm
  from orion.algo.space import Categorical, Dimension, Fidelity, Integer, Real, Space
  from orion.core.utils import format_trials
label_desc: Use image node_id 6 for calling the GridSearch obj's underlying member method code with example usage: obj.is_done() and returns: unknown