| Commit message (Collapse) | Author | Age |
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PiperOrigin-RevId: 201033171
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PiperOrigin-RevId: 201011811
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when unifying the nvcc/gcc and cuda-clang toolchains.
PiperOrigin-RevId: 200503048
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fixes in the patch have been incorporated into the Eigen opensource repository with this commit:
https://bitbucket.org/eigen/eigen/commits/60ab50654998f1cbe2791d49fea94d0ca5ae08a8
PiperOrigin-RevId: 199749536
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PiperOrigin-RevId: 199617749
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These rules currently get written by configure.py script to WORKSPACE
file which is not ideal since (1) WORKSPACE file is tracked by git and
(2) we require users to manually delete the rules in order to
update/regenerate them.
Moving these rules into an external repo that is generated based on
several ENV variables set by the configure.py script. Modifying any
of these ENV variables will cause the rules to be updated.
PiperOrigin-RevId: 199388460
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include the cuDNN header file.
PiperOrigin-RevId: 198869605
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Add BAZEL_SH environment variable as a dependency of python_configure repository rule
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* python_configure.bzl: Find bash binary path through BAZEL_SH env var.
This helps avoid invoking the wrong bash binary when "Bash on Ubuntu on Windows"
is installed.
Fixed https://github.com/tensorflow/tensorflow/issues/11735
* Readability modifications.
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Add missing deps for simd_armv8a in jpeg.BUILD
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Branch 197583446
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Enable mirror.bazel.build link for gemmlowp
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Revert #18413. Too many internal test failures due to the name scope change caused by this change.
Revert #18192. Cannot use re2::StringPiece internally. Need alternative for set call. Will pull and clean this up in a separate change.
PiperOrigin-RevId: 197991247
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Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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Use BUILD.bazel for third_party packages
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Building for armv8 fails with error:
ERROR: .../bazel/external/jpeg/BUILD:288:1: undeclared inclusion(s) in rule '@jpeg//:simd_armv8a':
this rule is missing dependency declarations for the following files included by 'external/jpeg/simd/jsimd_arm64.c':
'.../bazel/external/jpeg/jpegint.h'
'.../bazel/external/jpeg/jerror.h'
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Building Tensorflow on ppc64le fails with the message:
ERROR: /root/tensorflow/tensorflow/cc/BUILD:422:1: Linking of rule
'//tensorflow/cc:ops/control_flow_ops_gen_cc' failed (Exit 1)
bazel-out/host/bin/_solib_local/_U_S_Stensorflow_Scc_Cops_Scontrol_Uflow
_Uops_Ugen_Ucc___Utensorflow/libtensorflow_framework.so:
undefined reference to `png_init_filter_functions_vsx'
collect2: error: ld returned 1 exit status
This is fixed by adding powerpc specific files from the png archive
for @org_tensorflow//tensorflow:linux_ppc64le builds only.
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Both `BUILD` and `BUILD.bazel` could be used as the bazel project file
and `BUILD.bazel` is preferred (see https://github.com/bazelbuild/bazel/issues/4517#issuecomment-360213750)
This fix changes generated BUILD in third_party packages to `BUILD.bazel`.
This will help avoid conflict with `BUILD` or `build` file/directory names
in third party packages.
For example, while working on 19461 I noticed that apache thrift package
consists of a `build` directory and that causes issues in case-insensitive
systems like macOS. This PR should help avoid such conflict issues.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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PiperOrigin-RevId: 197817738
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Buildifier recently started sorting load args
https://github.com/bazelbuild/buildtools/commit/3ac5f85b22bc44820c041d0cacd3bc2ed54e7742 which causes diffs in the output.
PiperOrigin-RevId: 197556554
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gcc >= 7 will change how it treats -pie [1]; passing -pie after -shared
on the command line is not possible any more; given that the legacy way to
configure flags in the gcc/nvcc toolchain does not allow control over where
the flags go or how to provide -pie only for linking of binaries, we can
prevent this from breaking in the future by also using the new feature
mechanism for gcc/nvcc.
In addition to moving the gcc-specific workarounds in the toolchain to
cuda_configure.bzl, document them, so we don't need to rediscover them in the
future.
[1] https://gcc.gnu.org/bugzilla/show_bug.cgi?id=77464
PiperOrigin-RevId: 197522719
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s/tfe.enable_eager_execution/tf.enable_eager_execution/
PiperOrigin-RevId: 197500751
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PiperOrigin-RevId: 197121447
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* Fix issue #15588 by simplifying the code
The allocator.h code tried to be clever and use 32 byte alignment for SSE/AVX2/etc use,
and 64 byte alignment for AVX512.
Unfortunately, the #ifdef in use (from EIGEN) is not useful; the bazel BUILD files do
not propagate the tf_copts() compiler flags when the allocator.cc/allocator.h files get
compiled, to EIGEN does not see the actual AVX512 using compiler flags...
Rather than changing compiler flag propagation throughout a whole bunch of code,
there's an opportunity to just simplify the code and always use 64 byte alignment.
Yes it wastes a bit of space, but on the other hand now these allocations are
cache line aligned which isn't a bad thing... and an ifdef can be dropped
Signed-off-by: Arjan van de Ven <arjan@linux.intel.com>
* Set EIGEN_MAX_ALIGN_BYTES=64
This patch sets a 64 byte upper bound on the alignment of memory allocated by
eigen. This is necessary to prevent crashes during the execution of the unit
tests when they are compiled with AVX512 support.
Signed-off-by: Mark Ryan <mark.d.ryan@intel.com>
* Update the tensorflow/compiler/aot tests for 64 byte alignment
Modifications to the tensorflow/core/framework/allocator.h to always
use 64 byte alignment causes failures in the tensorflow/compiler/aot
unit tests. This patch updates these tests so that they pass with
64 byte aligned allocated memory.
Signed-off-by: Mark Ryan <mark.d.ryan@intel.com>
* Update Tensor.Slice_Basic for 64 byte alignment
The test case
//tensorflow/core:framework_tensor_test:Tensor.Slice_Basic
fails with EIGEN_MAX_ALIGN_BYTES set to 64. The reason is that the
slices it takes of the sample tensor are 32 byte and not 64 byte
aligned. This commit increases one of the dimensions of the original
tensor to ensure that the slices taken by the test cases are indeed 64
byte aligned.
Signed-off-by: Mark Ryan <mark.d.ryan@intel.com>
* Update ScopedAllocatorConcatOpTest.Reshape for 64 byte alignment
The ScopedAllocatorConcatOpTest.Reshape test requires that the elements
of the field_shapes parameter of ExecOp are multiples of
Allocator::kAllocatorAlignment in size. If they are not, the backing
tensor allocated by PrepOp will have too many elements and reshaping
will fail. This commit modifies the test case, making the elements
64 bytes in size, the new value for Allocator::kAllocatorAlignment.
Signed-off-by: Mark Ryan <mark.d.ryan@intel.com>
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lookup:lookup_ops_test and string_to_hash_bucket_op_test tests on ppc (#18414)
* Updating highwayhash library to fix kernel_tests:lookup_ops_test, lookup:lookup_ops_test and string_to_hash_bucket_op_test tests on ppc
* Fix endianess.h build on Windows
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This fix tries to address the issue raised in 19223
where the cupti.h eror message was misleading. The following error:
```
Cuda Configuration Error: Cannot find cupti.h under /usr/local/cuda-9.0
```
is not the true patch searched.
This fix updates the bzl file to print out the
complete searched paths when error occurs:
```
Cuda Configuration Error: Cannot find cupti.h under /usr/local/cuda-9.0/extras/CUPTI/include/, /usr/local/cuda-9.0/include/cuda/CUPTI/
```
This fix fixes 19223.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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PiperOrigin-RevId: 196387391
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PiperOrigin-RevId: 196349902
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PiperOrigin-RevId: 196205436
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PiperOrigin-RevId: 196020032
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PiperOrigin-RevId: 195849091
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This involves patching to override the png neon option. In the future
it might be worth enabling PNG optimization.
PiperOrigin-RevId: 195846513
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PiperOrigin-RevId: 195506194
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This is an error with clang trunk.
PiperOrigin-RevId: 195394277
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If building on a system that is not darwin, linux_x86_64, or
windows, the select statement in third_party/mkl/BUILD fails to
find a match and fails. Need to use no mkl libraries for non-x86
systems
Fixes #18084
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PiperOrigin-RevId: 195281004
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* fixed typos
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PiperOrigin-RevId: 194997009
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