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2024-03-15stop to support 32bit tensorflow-liteHEADmasterHongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15conf/layer.conf: add scarthgap to layers compatHongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15keras: upgrade keras to 2.16.0Hongxu Jia
According to [1]: Keras 2 remains available as the `tf-keras` package, still use `TF-Keras: the pure-TensorFlow implementation of Keras'[2] as usual [1] https://github.com/keras-team/keras/commit/d7268f3b32312cacd79d12b872ebb51ee98e6354 [2] https://github.com/keras-team/tf-keras Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15tensorflow/tensorflow-lite/tensorflow-native: clean up obsolete patchesHongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15tensorflow/tensorflow-lite/tensorflow-native: upgrade to 2.16.1Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15tensorboard: upgrade to 2.16.2Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15tensorflow-estimator: upgrade to 2.15.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-03-15clean up meta-demoHongxu Jia
The demos are obsolete and not maintained Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2024-01-08layer.conf: revert -> add dl layer to LAYERRECOMMENDSRandy MacLeod
The -dl (download) layers are not used anywhere but in Wind River products so drop the line that was added in: 5044996 layer.conf: add dl layer to LAYERRECOMMENDS Signed-off-by: Randy MacLeod <Randy.MacLeod@windriver.com>
2023-09-21tensorflow: fix build failure on aarch64Hongxu Jia
For cross compiling, run tf_python_api_gen at build time will fail which loads target library Build api_gen_binary_target as host tools and load native library at build time Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21tensorflow/tensorflow-lite: skip XNNPACK errorHongxu Jia
... root@intel-x86-64:~# label_image.lite INFO: Loaded model /usr/share/label_image/mobilenet_v1_1.0_224_quant.tflite INFO: resolved reporter INFO: Created TensorFlow Lite XNNPACK delegate for CPU. ERROR: failed to get XNNPACK profile information ... Build with option --define tflite_with_xnnpack=false to skip XNNPACK error Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21tensorboard: 2.12.0 -> 2.14.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21tensorflow-estimator: 2.12.0 -> 2.14.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21python3-mldtypes: add version 0.2.0Hongxu Jia
It is required by tensorflow 2.14.0 and keras 2.14.0 Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21keras: 2.12.0 -> 2.14.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21tensorflow/tensorflow-native/tensorflow-lite: 2.12.0 -> 2.14.0Hongxu Jia
- Drop obsolete patches: 0001-fix-compile-error-for-gcc-13.1.patch 0001-Revert-set-distinct_host_configuration-false-by-defa.patch - Add TF_NEED_CLANG=0 and TF_NEED_ROCM=0 to explicitly disable clang and rocm - Set CROSSTOOL_PYTHON_INCLUDE_PATH for tensorflow-native - Revert hermetic Python in Tensorflow, and use host python (python3-native) as depends in tensorflow - Fix build failure on gcc 13 (missing #include <cstdint>) Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21classes/bazel.bbclass: drop `build --linkopt=-Wl,-latomic' to fix build ↵Hongxu Jia
failure on gcc 13 Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-21bazel-native: 5.3.2 -> 6.0.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-13tensorflow-native: fix compieling failure on gcc 12mickledoreHongxu Jia
... /usr/include/bits/string_fortified.h:59:10: error: '__builtin_memset' may write between 16 and 2147483647 bytes into a region of size 15 [-Werror=stringop-overflow=] ... Add -Wno-stringop-overflow to host gcc Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-13classes/bazel.bbclass: fix build failure if USER not setHongxu Jia
... FATAL: $USER is not set, and unable to look up name of current user: (error: 0): Success ... Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-13bazel-native: fix compile failure on gcc 13Hongxu Jia
external/com_google_absl/absl/strings/internal/str_format/extension.h:34:33: error: found ':' in nested-name-specifier, expected '::' 34 | enum class FormatConversionChar : uint8_t; Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-09-13tensorflow: fix compile failureHongxu Jia
... tensorflow/tsl/platform/denormal.cc:20:1: note: 'uint32_t' is defined in header '<cstdint>'; did you forget to '#include <cstdint>'? 19 | #include "tensorflow/tsl/platform/platform.h" +++ |+#include <cstdint> ... Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-06-29bazel-native: disable uninativeHongxu Jia
The command bazel is a binary of a self-extracting zip file, call patchelf-uninative on it may break it occasionally ... bazel/bazel.real: Input/output error ... Due to commit [89bb76d bazel.bbclass: Fix build with bazel from sstate-cache] has called patchelf-uninative on the extracted binaries, disable uninative on bazel command Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-06-29tensorflow.inc: workaround compile error for gcc 13.1Hongxu Jia
After gcc is upgraded to 13.1, a compile error: |external/boringssl/src/crypto/bytestring/cbb.c:388:14: error: storing the address of local variable 'child' in '*cbb.child' [-Werror=dangling-pointer=] | 388 | cbb->child = out_contents; | | ~~~~~~~~~~~^~~~~~~~~~~~~~ Add -Wno-dangling-pointer to workaround the error ... |tensorflow/lite/kernels/internal/spectrogram.cc:46:22: error: 'uint32_t' was not declared in this scope | 46 | inline int Log2Floor(uint32_t n) { | ^~~~~~~~ |tensorflow/lite/kernels/internal/spectrogram.cc:20:1: note: 'uint32_t' is defined in header '<cstdint>'; did you forget to '#include <cstdint>'? ... Add '#include <cstdint>' Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-06-25conf/layer.conf: add mickledore to layers compatHongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-06-02bazel.bbclass: Fix build with bazel from sstate-cacheTomasz Dziendzielski
CAUTION: This email comes from a non Wind River email account! Do not click links or open attachments unless you recognize the sender and know the content is safe. Random errors can occur when bazel is taken from sstate-cache and the dynamic loader is no longer available. Setting DYNAMIC_LOADER and letting populate_sysroot_setscene modify the UNINATIVE_LOADER is not enough. That way we just modify the loader of bazel binary, but bazel is also a self-extracting zip file with built-in binaries that need dynamic loader modification to work. Eample error, as you can see it's quite misleading: | An error occurred during the fetch of repository 'local_config_cuda' | Cuda Configuration Error: Invalid cpu_value | Skipping 'tensorflow/lite/tools/benchmark:benchmark_model': no such package '@local_config_cuda//cuda To fix this in do_configure execute bazel version to unpack output_user_root and run patchelf-uninative on the ELF executables. Then change modification time to some future date so that bazel does not see the modification. Signed-off-by: Tomasz Dziendzielski <tomasz.dziendzielski@gmail.com>
2023-06-02bazel-native: Allow build from sstate-cacheTomasz Dziendzielski
CAUTION: This email comes from a non Wind River email account! Do not click links or open attachments unless you recognize the sender and know the content is safe. Using TOPDIR variable breaks the sstate-cache every time build directory changes totally breaking build from sstate-cache among different workspaces. Changing that to TMPDIR that is included in BB_HASHEXCLUDE_COMMON. Another thing is disabling the UNINATIVE_LOADER, causing sstate-cache artifacts not working in different workspaces. On populate_sysroot_setscene patchelf-uninative --set-interpreter with empty argument is ran which does not change the interpreter path and then bazel binary ends up with path to the interpreter that might not exist, since the bazel was taken from sstate-cache. Removing the UNINATIVE_LOADER = "" so that uninative.bbclass can correctly replace the interpreter path and make bazel binary usable. One could think that it will reintroduce the original issue behind disabling uninative, which was some java file corrupted (see commit dd7642b), but I think we don't have this problem anymore and also I don't think it was the correct solution - since the loader is anyway included in the binary, so it wasn't really disabling it, just disabling the yocto functionality around uninative. If the error re-occurs I think different solution should be found. Signed-off-by: Tomasz Dziendzielski <tomasz.dziendzielski@gmail.com>
2023-05-30add kirkstone to layers compatHongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-04-07tensorflow-lite: fix compile failure on axxiaarm/nxp-imx6Hongxu Jia
Replace qemuarm override to arm, apply the fix to all 32 bit arm BSPs Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-27tensorflow: Fix failure while gcc <= 7.5.0Hongxu Jia
Drop the revert patch, and fix the error directly |tensorflow/compiler/mlir/quantization/tensorflow/debugging/mlir_dump.cc:93:10: error: could not convert 'dump_file' from 'std::unique_ptr<llvm::raw_fd_ostream>' to 'absl::lts_20220623::StatusOr<std::unique_ptr<llvm::raw_fd_ostream> >' | return dump_file; ^~~~~~~~~ Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-24tensorflow-estimator: 2.12.0rc0 -> 2.12.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-24keras: 2.12.0rc1 -> 2.12.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-24tensorflow/tensorflow-lite/tensorflow-native: 2.12.0rc1 -> 2.12.0Hongxu Jia
The official tensorflow 2.12.0 is released [1], upgrade it [1] https://github.com/tensorflow/tensorflow/releases Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-23tensorflow: drop 0001-fix-XNNPACK-build-failure-for-qemuarm.patchHongxu Jia
The recipe tensorflow does not support qemuarm, so drop 0001-fix-XNNPACK-build-failure-for-qemuarm.patch Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-23tensorflow: ignore OE shared library resolverHongxu Jia
$ find packages-split/ -name libtensorflow_cc.so* packages-split/tensorflow-dbg/usr/lib64/.debug/libtensorflow_cc.so packages-split/tensorflow-dbg/usr/lib64/python3.11/site-packages/tensorflow/.debug/libtensorflow_cc.so.2 packages-split/libtensorflow-c/usr/lib64/libtensorflow_cc.so packages-split/python3-tensorflow/usr/lib64/python3.11/site-packages/tensorflow/libtensorflow_cc.so.2 Package libtensorflow-c provides /usr/lib64/libtensorflow_cc.so and package python3-tensorflow provides /usr/lib64/python3.11/ site-packages/tensorflow/libtensorflow_cc.so.2 The OE build system's shared library resolver incorrectly report the error of multiple shlib providers |ERROR: python3-tensorflow: Multiple shlib providers for libtensorflow_cc.so.2: libtensorflow-c, python3-tensorflow (used by files: tmp-glibc/work/ corei7-64-wrs-linux/tensorflow/2.12.0rc1-r0/packages-split/python3-tensorflow/ usr/lib64/python3.11/site-packages/tensorflow/python/_pywrap_tfe.so) Ignore OE shared library resolver Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-23tensorflow: skip 32bit arm supportHongxu Jia
It does not make sense to run tensorflow on 32 bit arm bsp. Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-23tensorflow: refresh 0001-fix-XNNPACK-build-failure-for-qemuarm.patch for ↵Hongxu Jia
2.12.0rc1 Signed-off-by: Hongxu Jia <hongxu.jia@windriver.com>
2023-03-22classes/bazel-base.bbclass: adjust default ram and cpu for bazelHongxu Jia
According to [1][2], adjust default ram and cpu for bazel, use 25% of them for bazel build [1] https://bazel.build/reference/command-line-reference#flag--local_ram_resources [2] https://bazel.build/reference/command-line-reference#flag--local_cpu_resources Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-21layer.conf: make recipe tensorflow/tensorflow-lite not be built for multilibHongxu Jia
For arm64 bsp, run 'bitbake lib32-tensorflow lib32-tensorflow-lite' caused mutilple compile failures, it does not make sense to build lib32-tensorflow, make recipe tensorflow not be built for multilib Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-21tensorflow: correct runtime depends of python3-tensorflowHongxu Jia
In commit [8235508 tensorflow: split sub packages], it split sub packages python3-tensorflow out of package tensorflow. This commit corrects the python3 runtime depends of packages python3-tensorflow Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-15Remove python 3.10.6 recipeHongxu Jia
The tensorflow 2.12 has supported python 3.11, remove old python3 Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-15tensorboard: 2.11.0 -> 2.12.0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-15tensorflow-estimator: 2.11 -> 2.12.0rc0Hongxu Jia
Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-15keras: 2.11.0 -> 2.12.0rc1Hongxu Jia
Drop obsolete patch: - 0001-support-to-compat-python-3.11.patch Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-15tensorflow/tensorflow-native: 2.11.0 -> 2.12.0rc1Hongxu Jia
Remove python 3.10 requirement checking, tensorflow 2.12 has supported python 3.11, remove old python 3.10 Refresh patches: - 0001-add-yocto-toolchain-to-support-cross-compiling.patch - 0001-support-32-bit-x64-and-arm-for-yocto.patch Drop obsolete patches: - 0003-Support-python-3.11-changes.patch - 0004-protobuf-fix-build-with-Python-3.11.patch - 0005-cpython-support-Python-3.11.patch - 0006-wrapt-support-Python-3.11.patch Add -Wno-stringop-overflow to CFLAGS to workaround gcc error Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2023-03-15python 3.10: add tomllibHongxu Jia
Backport patches from python 3.11 to add a new standard library module, `tomllib`, for parsing TOML. The implementation is based on Tomli (https://github.com/hukkin/tomli). Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2022-12-15bazel-native: 5.1.1 -> 5.3.2Hongxu Jia
Improve 0001-HttpDownloader-save-download-tarball-to-distdir.patch to fix download failure of tensorflow 2.11.0 Issue: LINUXEXEC-24074 (LOCAL REV: NOT UPSTREAM) -- will send to upstream Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2022-12-15tensorflow: fix offline build failureHongxu Jia
In tensorflow build, it downloads a full list of files, and Bazel won't cache the downloaded archive. But for Yocto, in order to support offline build ,we need to cache downloaded archive, so hardcode go SDKS list files rather than fetch from internet Issue: LINUXEXEC-24074 (LOCAL REV: NOT UPSTREAM) -- will send to upstream Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2022-12-15keras: 2.10.0 -> 2.11.0Hongxu Jia
Issue: LINUXEXEC-24074 (LOCAL REV: NOT UPSTREAM) -- will send to upstream Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
2022-12-15tensorflow-estimator: 2.10 -> 2.11Hongxu Jia
Issue: LINUXEXEC-24074 (LOCAL REV: NOT UPSTREAM) -- will send to upstream Signed-off-by: Hongxu Jia <hongxu.jia@eng.windriver.com>
generated by cgit 1.2.3-korg (git 2.39.0) at 2024-05-01 04:49:51 +0000