fix handling of replica parameters in DataParallel #33907
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mruberry
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Feb 27, 2020
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💊 CircleCI build failures summary and remediationsAs of commit d70e4cd (more details on the Dr. CI page):
🕵️ 10 new failures recognized by patternsThe following build failures do not appear to be due to upstream breakages (reran 8 jobs to discount flakiness):
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| Job | Step | Status |
|---|---|---|
 caffe2_onnx_py2_gcc5_ubuntu16_04_build |
Build |
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cc @suo. Jit tests are now passing because I don't delete an attribute for scripted module. However, scripted RNN+DataParallel did not work before this PR, and is still broken after. The reason behind this is scripting does not call overriden _apply from rnn module when moving scripted module to cuda, and does not call overriden setattr from rnn module when creating replicas, and generic implementations of those do not work for rnn (that's why we needed those overrides). |
suo
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mrshenli
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DDP was expecting .parameters() would return a all parameters of a replicated module. However, after pytorch#33907, we no longer populating _parameters for replicated modules. This PR fixes that problem by keeping params in a _former_parameters ordered dict on every module replica.
This was referenced May 11, 2020
cskyan
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…taParallel replicas. ([pytorch/pytorch#33907](pytorch/pytorch#33907))
cskyan
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…ataParallel replicas. (pytorch/pytorch#33907)
cskyan
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…ataParallel replicas. (pytorch/pytorch#33907) Same issue is reported at huggingface/transformers#3936
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In DataParallel, replica parameters are not leaves (because they are computed via broadcast from master parameters), and should be treated as such. Fixes #33552