class_docstr: Provenance tracking implementation in Pytorch.
  
  Provenance of the output tensor is the union of provenances of input tensors.
class_docstr_tok: ["Provenance","tracking","implementation","in","Pytorch",".","Provenance","of","the","output","tensor","is","the","union","of","provenances","of","input","tensors","."]
code: def __init__(self, data, provenance=frozenset()):
      assert isinstance(provenance, frozenset)
      if isinstance(data, ProvenanceTensor):
          provenance |= data._provenance
          data = data._t
      self._t = data
      self._provenance = provenance
  
imports: import torch
label_desc: Use image node_id 2 to create a new ProvenanceTensor object from inherited base classes: torch with example: obj = ProvenanceTensor(data, provenance)