Hacky support for meta tensor serialization. #62192
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This support is hacky because it doesn't preserve meta tensor storage sharing (e.g., if you serialize a model with shared storage, e.g., a tensor and a view on a tensor, when I deserialize the viewing relationship will be broken and these are just different tensors. Signed-off-by: Edward Z. Yang <ezyang@fb.com> [ghstack-poisoned]
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💊 CI failures summary and remediationsAs of commit 8c1a1a1 (more details on the Dr. CI page):
❄️ 1 failure tentatively classified as flakybut reruns have not yet been triggered to confirm:
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This support is hacky because it doesn't preserve meta tensor storage sharing (e.g., if you serialize a model with shared storage, e.g., a tensor and a view on a tensor, when I deserialize the viewing relationship will be broken and these are just different tensors. Signed-off-by: Edward Z. Yang <ezyang@fb.com> [ghstack-poisoned]
ezyang
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Jul 26, 2021
This support is hacky because it doesn't preserve meta tensor storage sharing (e.g., if you serialize a model with shared storage, e.g., a tensor and a view on a tensor, when I deserialize the viewing relationship will be broken and these are just different tensors. Signed-off-by: Edward Z. Yang <ezyang@fb.com> ghstack-source-id: 9ff1bc9 Pull Request resolved: #62192
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@ezyang has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
zou3519
approved these changes
Jul 26, 2021
albanD
approved these changes
Jul 26, 2021
| f.seek(0) | ||
| state = torch.load(f) | ||
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| self.assertEqual(state.weight.size(), big_model.weight.size()) |
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I think the tensor is plenty big enough :) I would certainly like it if we had more structured serialization tests for different device types, maybe a more involved refactor here is in order.
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Stack from ghstack:
This support is hacky because it doesn't preserve meta tensor storage
sharing (e.g., if you serialize a model with shared storage, e.g., a
tensor and a view on a tensor, when I deserialize the viewing
relationship will be broken and these are just different tensors.) The
hack is also durable, in the sense that we will be on the hook for
supporting
_rebuild_meta_tensor_no_storagein perpetuity in thefuture, even if we change our mind about the serialization format.
This unblocks an FB production use case. I didn't add C++ support to minimize
blast area of this patch.
Signed-off-by: Edward Z. Yang ezyang@fb.com
Differential Revision: D29910535