| Commit message (Collapse) | Author | Age |
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Please approve this CL. It will be submitted automatically, and its GitHub pull request will be marked as merged.
Imported from GitHub PR #21373
A new version of nsync is released, this updates the workspace.bzl and adds nsync to the libs that can be unbundled. I've packaged nsync on Gentoo Linux and tested the full unbundled build.
The CMake build is also updated to the latest version, the patch is no longer required and is removed. I have tested the cmake build on my machine but the CI needs to test windows since I can't.
The last commits update ./configure to handle adding TF_SYSTEM_LIBS and an option to disable stripping.
@m3bm3b, can you review too?
Copybara import of the project:
- 3d224b29fcf699b84cf538e2d16e3dd4e78e6a91 workspace: update nsync dep to 1.20.1 by Jason Zaman <jason@perfinion.com>
- 34536b88bedc5a83ad939438a49a3cc53aea210c CMake: nsync: update to 1.20.1 by Jason Zaman <jason@perfinion.com>
- f2444ba218ae280e03710f936b249b6b650ea3dd third_party: unbundle nsync by Jason Zaman <jason@perfinion.com>
- 4386d8c4b01020ba1c979258e5102ac1947d2574 configure: Add TF_SYSTEM_LIBS handling by Jason Zaman <jason@perfinion.com>
- f3fd1f110781cfb8cc941241a69eb41114787bfd Merge 4386d8c4b01020ba1c979258e5102ac1947d2574 into a05c7... by Jason Zaman <jasonzaman@gmail.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/21373 from perfinion:nsync 4386d8c4b01020ba1c979258e5102ac1947d2574
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PiperOrigin-RevId: 208913262
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Previously, specifying --define=using_mkl_dnn_only=true would cause
MKL-ML-dependent code to be #ifdef'd out, but dependencies on MKL-ML itself
would still be present. This change makes all library dependencies on MKL
properly select MKL-ML, MKL-DNN, or both, depending on the selected
configuration.
PiperOrigin-RevId: 208710102
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PiperOrigin-RevId: 208509699
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Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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This fix updates librdkafka to 0.11.5.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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Revert #18293.
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I previously use hacky BUILD file to import prebuilt LLVM binaries from CMake to Bazel so that I can build `tfcompile` with Bazel on Windows, but since Tensorflow updates the LLVM revision used very frequently, this method is too troublesome.
I am trying to make XLA/AOT to work out-of-the-box on Windows with Bazel, then convince Tensorflow team to create a presubmit so that no one can break XLA/AOT on Windows anymore.
Summary:
- Remove unused `llvm_host_triple`.
- Rename `cmake_vars` to `posix_cmake_vars` and create a new `win32_cmake_vars` as Windows is sufficiently different from other platforms.
- Create `LLVM_DEFINES`, `LLVM_COPTS` and `LLVM_LINKOPTS` in `llvm.bzl` to set global compile/link flags for LLVM.
- Create macro `llvm_cc_library` that wrap around `cc_library` to ensure that all targets receive `LLVM_COPTS` consistently. Replace all `cc_library` with `llvm_cc_library`.
- For `support` library, include `lib/Support/Windows/*` for Windows and `lib/Support/Unix/*` for others.
If `llvm.BUILD` is not to be edited manually no matter what, can the script used to generate `llvm.BUILD` be open-sourced?
#15213
/cc @tatatodd
Imported from GitHub PR #18293
Copybara import of the project:
- a5e7b841d79878b12e0d0103e5b1813384a80aa8 [XLA/AOT] Build LLVM with Bazel on Windows by Loo Rong Jie <loorongjie@gmail.com>
- b3a20c7bbff95fd8ad9f44c653a3ecffc54de3b3 Add back LLVM_ENABLE_STATS by Loo Rong Jie <loorongjie@gmail.com>
- 787d451b495180f5c882d09d76222c157102f0fc Merge b3a20c7bbff95fd8ad9f44c653a3ecffc54de3b3 into 6a1ff... by Loo Rong Jie <loorongjie@gmail.com>
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/18293 from rongjiecomputer:llvm b3a20c7bbff95fd8ad9f44c653a3ecffc54de3b3
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based on PR review comments.
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instead of glob-of-select. This was suggested in
https://github.com/tensorflow/tensorflow/commit/add96c8632df9596a73bf637d6b7015e9c7beaad#r29707275
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PiperOrigin-RevId: 206240947
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PiperOrigin-RevId: 206209252
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tensorflow/tools/ci_build/install/install_pip_packages.sh
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* Added nGraph bridge as a third_party to be built with TensorFlow based on user selection.
* Added a limited set of C++ unit tests to verify the correctness of the computation
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PiperOrigin-RevId: 205248470
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Also adds arguments to control distributed aggregation to the tf.Variable constructor.
Removes tfe.Variable from examples as it's now unnecessary.
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https://github.com/intel/mkl-dnn/blob/master/LICENSE
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Merge pull request #20749
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PiperOrigin-RevId: 204530874
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Signed-off-by: Jason Zaman <jason@perfinion.com>
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The jsoncpp headers are included with a different path so we have to
symlink them so the are in the dir structure that is expected.
Signed-off-by: Jason Zaman <jason@perfinion.com>
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