Implement weight as part of the allreduce protocol, not matchmaking #384
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@@ Coverage Diff @@
## master #384 +/- ##
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- Coverage 84.04% 84.02% -0.03%
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Files 70 70
Lines 6426 6423 -3
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- Hits 5401 5397 -4
- Misses 1025 1026 +1
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justheuristic
changed the title
justheuristic
commented
Sep 18, 2021
| @@ -37,13 +38,12 @@ class AllReduceRunner(ServicerBase): | |||
| :param prefix: namespace for servicer's RPCs (typically, equal to prefix for group keys) | |||
| :param group_id: unique identifier of this specific all-reduce run | |||
| :param tensors: local tensors that should be averaged with groupmates | |||
| :param tensors: local tensors that should be averaged with groupmates | |||
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yeah, that was in the master code :)
borzunov
requested changes
Sep 20, 2021
hivemind/averaging/allreduce.py
Outdated
| @@ -180,9 +182,10 @@ async def _generate_input_for_peer(self, peer_index: int) -> AsyncIterator[avera | |||
| code=averaging_pb2.PART_FOR_AVERAGING, | |||
| group_id=self.group_id, | |||
| tensor_part=first_part, | |||
| metadata=self._weight_binary, | |||
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Can we create a new double weight; field instead and avoid encoding the weight to the binary format manually?
borzunov
approved these changes
Sep 24, 2021
Co-authored-by: Alexander Borzunov <[email protected]>
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This PR allows specifying allreduce weights in AllReduceRunner, instead of gathering them during matchmaking.
This will allow peers to use their actual batch size in both DPU and advance matchmaking (aka @yhn112 -style matchmaking)
[WIP] implement advance matchmaking as a working example