class_docstr: Class used to either find the subset of IDs that are in this
  filter, or the subset of IDs that are not in this filter
  given a second set of IDs.
  
  Examples
  --------
  >>> import torch as th
  >>> from dgl.utils import Filter
  >>> f = Filter(th.tensor([3,2,9], device=th.device('cuda')))
  >>> f.find_included_indices(th.tensor([0,2,8,9], device=th.device('cuda')))
  tensor([1,3])
  >>> f.find_excluded_indices(th.tensor([0,2,8,9], device=th.device('cuda')))
  tensor([0,2], device='cuda')
docstr: Create a new filter from a given set of IDs. This currently is only
  implemented for the GPU.
  
  Parameters
  ----------
  ids : IdArray
      The unique set of IDs to keep in the filter.
docstr_tok: ["Create","a","new","filter","from","a","given","set","of","IDs",".","This","currently","is","only","implemented","for","the","GPU",".","Parameters","--","--","--","--","--","ids",":","IdArray","The","unique","set","of","IDs","to","keep","in","the","filter","."]
code: def __init__(self, ids):
      """Create a new filter from a given set of IDs. This currently is only
      implemented for the GPU.
  
      Parameters
      ----------
      ids : IdArray
          The unique set of IDs to keep in the filter.
      """
      self._filter = _CAPI_DGLFilterCreateFromSet(
          F.zerocopy_to_dgl_ndarray(ids)
      )
  
imports: from ..None import backend
  from .._ffi.function import _init_api
label_desc: Use image node_id 1 to create a new Filter object from inherited base classes: object with example: obj = Filter(ids)