parameters: (x, level)
return_statement: return qpts
docstring: r"""Quantize :math:`[-1, 1]` float coordinates in to
      :math:`[0, (2^{level})-1]` integer coords.
  
      If a point is out of the range :math:`[-1, 1]` it will be clipped to it.
  
      Args:
          x (torch.FloatTensor): Floating point coordinates,
                                 must be of last dimension 3.
          level (int): Level of the grid
  
      Returns
          (torch.ShortTensor): Quantized 3D points, of same shape than x.
docstring_summary: r"""Quantize :math:`[-1, 1]` float coordinates in to
      :math:`[0, (2^{level})-1]` integer coords.
docstring_tokens: r Quantize : math : [ - 1 1 ] float coordinates in to : math : [ 0 ( 2^ { level } ) - 1 ] integer coords .
function: def quantize_points(x, level):
      r"""Quantize :math:`[-1, 1]` float coordinates in to
      :math:`[0, (2^{level})-1]` integer coords.
  
      If a point is out of the range :math:`[-1, 1]` it will be clipped to it.
  
      Args:
          x (torch.FloatTensor): Floating point coordinates,
                                 must be of last dimension 3.
          level (int): Level of the grid
  
      Returns
          (torch.ShortTensor): Quantized 3D points, of same shape than x.
      """
      res = 2 ** level
      qpts = torch.floor(torch.clamp(res * (x + 1.0) / 2.0, 0, res - 1.)).short()
      return qpts
function_tokens: def quantize_points ( x , level ) : res = 2 ** level qpts = torch . floor ( torch . clamp ( res * ( x + 1.0 ) / 2.0 , 0 , res - 1. ) ) . short ( ) return qpts