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ci/official/envs/linux_x86_tpu
source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu" TFCI_LIB_SUFFIX="-tpu-linux-x86_64" TFCI_WHL_BAZEL_TEST_ENABLE=0 TFCI_WHL_IMPORT_TEST_ENABLE=0 TFCI_WHL_SIZE_LIMIT=580M
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.bazelrc
build:linux --copt="-Wno-array-bounds" # Add unused-result as an error on Linux. build:linux --copt="-Wunused-result" build:linux --copt="-Werror=unused-result" # Add switch as an error on Linux. build:linux --copt="-Wswitch" build:linux --copt="-Werror=switch" # Required for building with clang build:linux --copt="-Wno-error=unused-but-set-variable" # Linux ARM64 specific options
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tensorflow/c/experimental/filesystem/plugins/posix/BUILD
hdrs = ["posix_filesystem_helper.h"], deps = [":copy_file"], ) # On Linux, we can copy files faster using `sendfile`. But not elsewhere. # Hence, this private library to select which implementation to use. cc_library( name = "copy_file", srcs = select({ "//tensorflow:linux_x86_64": ["copy_file_linux.cc"], "//conditions:default": ["copy_file_portable.cc"], }), hdrs = ["copy_file.h"],
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.github/workflows/arm-cd.yml
- r2.** schedule: - cron: '0 8 * * *' permissions: contents: read jobs: build: if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks runs-on: [self-hosted, linux, ARM64] strategy: fail-fast: false matrix: pyver: ['3.9', '3.10', '3.11', '3.12'] steps: - name: Stop old running containers (if any) shell: bash run: |
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tensorflow/BUILD
) # This condition takes precedence over :linux_x86_64 config_setting( name = "linux_x86_64_no_sse", values = { "cpu": "k8", "copt": "-mno-sse4.2", }, visibility = ["//visibility:public"], ) # This condition takes precedence over :linux_x86_64 # TODO(b/290533709): Remove this with PJRT build rule cleanup. config_setting( name = "linux_x86_64_with_weightwatcher",
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.github/workflows/arm-ci-extended.yml
- v2.** schedule: - cron: '0 4 * * *' permissions: contents: read jobs: build: if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks runs-on: [self-hosted, linux, ARM64] strategy: fail-fast: false matrix: pyver: ['3.9', '3.10', '3.11', '3.12'] steps: - name: Stop old running containers (if any) shell: bash run: |
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configure.py
_DEFAULT_PROMPT_ASK_ATTEMPTS = 10 _TF_BAZELRC_FILENAME = '.tf_configure.bazelrc' _TF_WORKSPACE_ROOT = '' _TF_BAZELRC = '' _TF_CURRENT_BAZEL_VERSION = None NCCL_LIB_PATHS = [ 'lib64/', 'lib/powerpc64le-linux-gnu/', 'lib/x86_64-linux-gnu/', '' ] # List of files to configure when building Bazel on Apple platforms. APPLE_BAZEL_FILES = [ 'tensorflow/lite/ios/BUILD', 'tensorflow/lite/objc/BUILD', 'tensorflow/lite/swift/BUILD',
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1) -
ci/official/utilities/code_check_full.bats
# # We can't test on the windows toolchains because they're using a legacy # toolchain format (or something) that specifies the toolchain directly instead # of as a "repository". They can't be valid on Linux because Linux can't do # anything with a Windows-only toolchain, and bazel errors if trying to build # that directory. @test "bazel nobuild passes on all of TF except TF Lite and win toolchains" {
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CONTRIBUTING.md
```bash bazel build --config=dbg //tensorflow/tools/pip_package:build_pip_package ``` TensorFlow kernels and TensorFlow's dependencies are still not built with debugging information with `--config=dbg`, as issues occur on Linux if there is too much debug info (see [this GitHub issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If you want to debug a kernel, you can compile specific files with `-g` using the
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RELEASE.md
* [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md) are available in Linux x86, Windows x86, and Linux aarch64 packages. * **Linux x86 packages:** * oneDNN optimizations are *enabled by default* on CPUs with neural-network-focused hardware features such as AVX512_VNNI,
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