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beginner_source/blitz/autograd_tutorial.py
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implementation - a ``Function``.
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``Tensor`` and ``Function`` are interconnected and build up an acyclic
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-graph, that encodes a complete history of computation. Each variable has
+graph, that encodes a complete history of computation. Each tensor has
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a ``.grad_fn`` attribute that references a ``Function`` that has created
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the ``Tensor`` (except for Tensors created by the user - their
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``grad_fn is None``).
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