Update node metas after parallelization #84
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| local_args = [] | ||
| for placeholder, arg in zip(gm.graph.nodes, args): | ||
| assert placeholder.meta["val"].shape == arg.shape | ||
| local_arg = arg.to_local() | ||
| placeholder.meta["val"] = local_arg | ||
| # requires_grad is missing from val and local_arg, take it | ||
| # from original tensor_meta | ||
| requires_grad = placeholder.meta["tensor_meta"].requires_grad | ||
| placeholder.meta["tensor_meta"] = _extract_tensor_metadata( | ||
| local_arg.clone().requires_grad_(requires_grad) | ||
| ) | ||
| local_args.append(local_arg) |
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I think this is wrong, and we would need to implement this after we construct the parameters, otherwise we end-up sharding the model twice
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you are correct. I confirmed that after running make_fx on sharding interpreter, the new parallel_gm0 has its metas updated. I am not sure why i (thought I) had to do this update in hack_aot.
TODO: test this somehow
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abandoned because I had to move these changes into the compile PR to land together |
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TODO: