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| # _unsafe_view is not tagged as a view op but is semantically a reshape; | ||
| # its non-tensor shape args become invalid after sharding so skip costing. | ||
| if node.target == torch.ops.aten._unsafe_view.default: |
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Shouldn't this be fixed in PyTorch? I'd expect _unsafe_view to have the is_view tag set?
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IIUC, this is intentional? this flag prevents AOTAutograd from doing all the view-replay needed for functionalization.
// NOTE [ Unsafe View ]
// _unsafe_view() differs from view() in that the returned tensor isn't treated
// as a view for the purposes of automatic differentiation. (It's not listed in
// VIEW_FUNCTIONS in gen_inplace_or_view_type.py). It's only safe to use if the
// `self` tensor is temporary. For example, the viewed tensor here (a + b) is
// discarded immediately after viewing:
//
// res = at::_unsafe_view(a + b, size);
//
// This is a hack because in-place operations on tensors treated like views
// can be much more expensive than the same operations on non-view tensors.
But I think for autoparallel you want the "is_view", 0-cost semantics
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