parameters: (point, point_cloud)
return_statement: return np.linalg.norm(point_cloud - point, axis=2)
docstring: Estimates the distance of a point to every point in a point cloud.
  
    Args:
      point: a 3D vector representing a point.
      point_cloud: a point cloud represented as an 2D array of which has the shape
        of [m, n, 3].
  
    Returns:
      distances: a distance field represented as a 2D array [m, n].
docstring_summary: Estimates the distance of a point to every point in a point cloud.
docstring_tokens: Estimates the distance of a point to every point in a point cloud .
function: def point_cloud_distances(point, point_cloud):
    """Estimates the distance of a point to every point in a point cloud.
  
    Args:
      point: a 3D vector representing a point.
      point_cloud: a point cloud represented as an 2D array of which has the shape
        of [m, n, 3].
  
    Returns:
      distances: a distance field represented as a 2D array [m, n].
    """
    return np.linalg.norm(point_cloud - point, axis=2)
function_tokens: def point_cloud_distances ( point , point_cloud ) : return np . linalg . norm ( point_cloud - point , axis = 2 )