code: def choose_grid_size(
      train_inputs, ratio=1.0, kronecker_structure=True
  ):
      """
      Given some training inputs, determine a good grid size for KISS-GP.
  
      :param x: the input data
      :type x: torch.Tensor (... x n x d)
      :param ratio: Amount of grid points per data point (default: 1.)
      :type ratio: float, optional
      :param kronecker_structure: Whether or not the model will use Kronecker structure in the grid
          (set to True unless there is an additive or product decomposition in the prior)
      :type kronecker_structure: bool, optional
      :return: Grid size
      :rtype: int
      """
      # Scale features so they fit inside grid bounds
      num_data = (
          train_inputs.numel()
          if train_inputs.dim() == 1
          else train_inputs.size(-2)
      )
      num_dim = 1 if train_inputs.dim() == 1 else train_inputs.size(-1)
      if kronecker_structure:
          return int(ratio * math.pow(num_data, 1.0 / num_dim))
      else:
          return ratio * num_data
  
file_path: gpytorch/gpytorch/utils/grid.py
imports: import math
  import warnings
  from typing import List, Tuple
  import torch
label_desc: Use image node_id 2 for calling a global function with example usage: choose_grid_size(train_inputs, ratio, kronecker_structure) and returns: int, unknown