class_docstr: Feature storage object which should support a fetch() operation.  It is the
  counterpart of a tensor for homogeneous graphs, or a dict of tensor for heterogeneous
  graphs where the keys are node/edge types.
class_docstr_tok: ["Feature","storage","object","which","should","support","a","fetch","(",")","operation",".","It","is","the","counterpart","of","a","tensor","for","homogeneous","graphs",",","or","a","dict","of","tensor","for","heterogeneous","graphs","where","the","keys","are","node\/edge","types","."]
docstr: Whether the FeatureStorage requires the DataLoader to set use_ddp.
docstr_tok: ["Whether","the","FeatureStorage","requires","the","DataLoader","to","set","use_ddp","."]
code: def requires_ddp(self):
      """Whether the FeatureStorage requires the DataLoader to set use_ddp."""
      return False
  
file_path: dgl/python/dgl/storages/base.py
imports: import threading
label_desc: Use image node_id 1 for calling the FeatureStorage obj's underlying member method code with example usage: obj.requires_ddp() and returns: False