{"push_id":3085242422,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"a3cfab2d63c1316b74ca26406a7055dba6b39750","before":"49fe678feca88e030f541eb7106e09996de4725a","commits":[{"sha":"a3cfab2d63c1316b74ca26406a7055dba6b39750","author":{"name":"Jongsoo Park","email":"9a3e35cef3c98d8190c15db076afab6069cc7549@fb.com"},"message":"per-group and per-channel quantization (#14340)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/14340\n\nPull Request resolved: https://github.com/pytorch/FBGEMM/pull/25\n\nPer-group and per-channel quantization in fbgemm\nThis diff also cleans up explicit template instantiation using macro expansion\nThis diff also changes randFill interface which was easy to make mistakes of generating integer random numbers for floating point vectors.\n\nUsing this in DNNLOWP operators will be done in a separate diff.\n\nReviewed By: dskhudia\n\nDifferential Revision: D13176386\n\nfbshipit-source-id: e46c53e31e21520bded71b8ed86e8b19e010e2dd","distinct":true,"url":"https://api.github.com/repos/pytorch/pytorch/commits/a3cfab2d63c1316b74ca26406a7055dba6b39750"}]}
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