Multitple fixes to MC modules to facilitate integration #1391
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Summary: Some bug fixes during the integration test in PyPER O3: ### fix pytorch#1 `_embedding_bag_collection` (`ShardedEmbeddingBagCollection`) is not really called by input_dist (because the same thing is already distributed by ShardedManagedCollisionCollection) . So it never get a chance to initiate `_input_dist`. As a result, TREC pipelining thinks it's not ready for input distribution. This is not expected, since the module is not used in the stage anyway, nor should it be put in fused a2a communication. With this change, https://fburl.com/code/ud8lnixv it'll satisfy the assertion, meanwhile doesn't carry _input_dists so won't be put into fused a2a. ### fix pytorch#2 ManagedCollisionCollection.forward is not traceable because it uses unwarpped `KeyedJaggedTensor.from_jt_dict`. We don't care about its internal detail so just keep it atomic. ### fix pytorch#3 Due to how remap table is set, `MCHManagedCollisionModule` doesn't support i32 id list for now. An easy fix is to convert to i64 regardless. A more memory efficient fix is probably change the remapper to i32 if necessary Differential Revision: D48804332
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Summary: Some bug fixes during the integration test in PyPER O3: ### fix pytorch#1 `_embedding_bag_collection` (`ShardedEmbeddingBagCollection`) is not really called by input_dist (because the same thing is already distributed by ShardedManagedCollisionCollection) . So it never get a chance to initiate `_input_dist`. As a result, TREC pipelining thinks it's not ready for input distribution. This is not expected, since the module is not used in the stage anyway, nor should it be put in fused a2a communication. With this change, https://fburl.com/code/ud8lnixv it'll satisfy the assertion, meanwhile doesn't carry _input_dists so won't be put into fused a2a. ### fix pytorch#2 ManagedCollisionCollection.forward is not traceable because it uses unwarpped `KeyedJaggedTensor.from_jt_dict`. We don't care about its internal detail so just keep it atomic. ### fix pytorch#3 Due to how remap table is set, `MCHManagedCollisionModule` doesn't support i32 id list for now. An easy fix is to convert to i64 regardless. A more memory efficient fix is probably change the remapper to i32 if necessary Differential Revision: D48804332
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Summary: Some bug fixes during the integration test in PyPER O3: ### fix pytorch#1 `_embedding_bag_collection` (`ShardedEmbeddingBagCollection`) is not really called by input_dist (because the same thing is already distributed by ShardedManagedCollisionCollection) . So it never get a chance to initiate `_input_dist`. As a result, TREC pipelining thinks it's not ready for input distribution. This is not expected, since the module is not used in the stage anyway, nor should it be put in fused a2a communication. With this change, https://fburl.com/code/ud8lnixv it'll satisfy the assertion, meanwhile doesn't carry _input_dists so won't be put into fused a2a. ### fix pytorch#2 ManagedCollisionCollection.forward is not traceable because it uses unwarpped `KeyedJaggedTensor.from_jt_dict`. We don't care about its internal detail so just keep it atomic. ### fix pytorch#3 Due to how remap table is set, `MCHManagedCollisionModule` doesn't support i32 id list for now. An easy fix is to convert to i64 regardless. A more memory efficient fix is probably change the remapper to i32 if necessary Differential Revision: D48804332
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Summary:
Some bug fixes during the integration test in PyPER O3:
fix #1
_embedding_bag_collection(ShardedEmbeddingBagCollection) is not really called by input_dist (because the same thing is already distributed by ShardedManagedCollisionCollection) . So it never get a chance to initiate_input_dist. As a result, TREC pipelining thinks it's not ready for input distribution.This is not expected, since the module is not used in the stage anyway, nor should it be put in fused a2a communication. With this change, https://fburl.com/code/ud8lnixv it'll satisfy the assertion, meanwhile doesn't carry _input_dists so won't be put into fused a2a.
fix #2
ManagedCollisionCollection.forward is not traceable because it uses unwarpped
KeyedJaggedTensor.from_jt_dict. We don't care about its internal detail so just keep it atomic.fix #3
Due to how remap table is set,
MCHManagedCollisionModuledoesn't support i32 id list for now. An easy fix is to convert to i64 regardless. A more memory efficient fix is probably change the remapper to i32 if necessaryDifferential Revision: D48804332