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Updated libxsmm kernels - #10112

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benoitsteiner merged 3 commits into
tensorflow:masterfrom
benoitsteiner:master
May 22, 2017
Merged

benoitsteiner merged 3 commits into
tensorflow:masterfrom
benoitsteiner:master

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benoitsteiner requested a review from gunan May 22, 2017 19:30
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We found a Contributor License Agreement for you (the sender of this pull request), but were unable to find agreements for the commit author(s). If you authored these, maybe you used a different email address in the git commits than was used to sign the CLA (login here to double check)? If these were authored by someone else, then they will need to sign a CLA as well, and confirm that they're okay with these being contributed to Google.

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gunan commented May 22, 2017

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Just to make sure. do we have a CLA in place for @hfp?

hfp added 3 commits May 22, 2017 12:50
…SMM_DNN_CONV_OPTION_OVERWRITE. (tensorflow#26)

* Fixed AVX-512 intrinsic implementation.

* OR'ed LIBXSMM_DNN_CONV_OPTION_OVERWRITE into convolution options, which folds zeroing the input buffer on first use. This removes the call to libxsmm_dnn_zero_buffer in case of LIBXSMM_DNN_COMPUTE_KIND_FWD.
…ase of LIBXSMM_DNN_WARN_FALLBACK, use libxsmm_hash instead of std::hash, code cleanup (tensorflow#27)

* Fixed AVX-512 intrinsic implementation.

* OR'ed LIBXSMM_DNN_CONV_OPTION_OVERWRITE into convolution options, which folds zeroing the input buffer on first use. This removes the call to libxsmm_dnn_zero_buffer in case of LIBXSMM_DNN_COMPUTE_KIND_FWD.

* Rely on libxsmm_hash rather than std::hash. Brought xsmm_conv2d.cc up-to-date with TF/master.

* Code cleanup: use LIBXSMM_DNN_CONV_OPTION_WU_EXT_FILTER_REDUCE_OVERWRITE rather than assembling the option from separate flags.

* Avoid to destroy the handle in case of LIBXSMM_DNN_WARN_FALLBACK since the next iteration may double-delete the same handle. One would need to update the handle-cache to allow destruction at this place. However, all handles are destructed when TF terminates (cache cleanup).
* Fixed AVX-512 intrinsic implementation.

* OR'ed LIBXSMM_DNN_CONV_OPTION_OVERWRITE into convolution options, which folds zeroing the input buffer on first use. This removes the call to libxsmm_dnn_zero_buffer in case of LIBXSMM_DNN_COMPUTE_KIND_FWD.

* Rely on libxsmm_hash rather than std::hash. Brought xsmm_conv2d.cc up-to-date with TF/master.

* Code cleanup: use LIBXSMM_DNN_CONV_OPTION_WU_EXT_FILTER_REDUCE_OVERWRITE rather than assembling the option from separate flags.

* Avoid to destroy the handle in case of LIBXSMM_DNN_WARN_FALLBACK since the next iteration may double-delete the same handle. One would need to update the handle-cache to allow destruction at this place. However, all handles are destructed when TF terminates (cache cleanup).

* Rely on default configuration arguments, and thereby lower the dependence from LIBXSMM internals.
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So there's good news and bad news.

👍 The good news is that everyone that needs to sign a CLA (the pull request submitter and all commit authors) have done so. Everything is all good there.

😕 The bad news is that it appears that one or more commits were authored by someone other than the pull request submitter. We need to confirm that they're okay with their commits being contributed to this project. Please have them confirm that here in the pull request.

Note to project maintainer: This is a terminal state, meaning the cla/google commit status will not change from this state. It's up to you to confirm consent of the commit author(s) and merge this pull request when appropriate.

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We have a CLA in place with @hfp

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benoitsteiner merged commit 23caaa5 into tensorflow:master May 22, 2017
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4 participants