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8b4ae29b1b
Handling of nested modules in unflatten had several bugs, which were caught by trying to preserve module call signatures for nested modules. * A module `k` encountered when calling `k.n()` before `k()` used to become an empty nn module. This caused some information to be dropped when `k()` was eventually called. Relatedly, we would also lose call counts for `k.n()` through different paths (say, when `k()` calls `n()`). * Deleting call-indexed modules and patching up their call sites was broken for nested modules when creating dispatcher modules, because of silliness when handling their fqns. An interesting aside is that we used random graph generation for testing some of these changes. A future PR will add the infra to create tests using these random graphs. Differential Revision: D66192799 Pull Request resolved: https://github.com/pytorch/pytorch/pull/141066 Approved by: https://github.com/angelayi |
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| .. | ||
| _composable | ||
| _shard | ||
| _sharded_tensor | ||
| _sharding_spec | ||
| _symmetric_memory | ||
| _tensor | ||
| _tools | ||
| algorithms | ||
| autograd | ||
| benchmarks | ||
| checkpoint | ||
| elastic | ||
| examples | ||
| fsdp | ||
| launcher | ||
| nn | ||
| optim | ||
| pipelining | ||
| rpc | ||
| tensor | ||
| __init__.py | ||
| _checkpointable.py | ||
| _composable_state.py | ||
| _functional_collectives_impl.py | ||
| _functional_collectives.py | ||
| _state_dict_utils.py | ||
| argparse_util.py | ||
| c10d_logger.py | ||
| collective_utils.py | ||
| constants.py | ||
| CONTRIBUTING.md | ||
| device_mesh.py | ||
| distributed_c10d.py | ||
| launch.py | ||
| logging_handlers.py | ||
| remote_device.py | ||
| rendezvous.py | ||
| run.py | ||
| utils.py | ||