Implementation of MatMul with bias operator for MKL-DNN #20136
Conversation
pytorchbot
added
caffe2
module: pybind
|
@bddppq This is how we leverage inner_product to do matrix multiplication in C2. FYI. |
Matrix multiplication with bias $Y = A * B + Bias$, where `A` has size (M x K) or (Batch_size x M x k), `B` has size (K x N), `Bias` has size (n), and `Y` will have a size (M x N) or (Batch_size x M x N). To transpose `A` or `B` before multiplication, pass 1 to the `trans_a` and/or `trans_b` arguments, which separate the first and second dimensions of the respective matrices using `axis_a` and `axis_b`. This patch depend on pytorch#19955. Change-Id: Iea33d609f814a062d4e2b1b48a96e8a1da9f1072
|
this PR depends on #20569 now. |
|
Hi @PenghuiCheng! Thank you for your pull request and welcome to our community. Action RequiredIn order to merge any pull request (code, docs, etc.), we require contributors to sign our Contributor License Agreement, and we don't seem to have one on file for you. ProcessIn order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA. Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with If you have received this in error or have any questions, please contact us at cla@fb.com. Thanks! |
|
Looks like this PR hasn't been updated in a while so we're going to go ahead and mark this as |
6 participants
Matrix multiplication with bias$Y = A * B + Bias$ , where
Ahas size (M x K) or (Batch_size x M x k),Bhas size (K x N),Biashas size (n), andYwill have a size (M x N) or (Batch_size x M x N). To transposeAorBbefore multiplication, pass 1 to thetrans_aand/ortrans_barguments, which separate the first and second dimensions of the respective matrices usingaxis_aandaxis_b.This patch depend on #19955.
Change-Id: Iea33d609f814a062d4e2b1b48a96e8a1da9f1072