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ci/official/wheel_test/WORKSPACE
workspace(name = "wheel_test") # buildifier: disable=load-on-top load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") http_archive( name = "bazel_skylib", sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506", urls = [ "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
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ci/official/envs/public_cache_push
# Sourcing this enables Bazel remote cache (read and write) # Note that "_push" cache configs write to GCS buckets and require # authentication. If you are not a Googler, source "public_cache" to enable the # public read-only cache. # The cache configs are different for MacOS and Linux if [[ $(uname -s) == "Darwin" ]]; then TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache_push" else
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ci/official/utilities/setup_macos.sh
exit 1 fi # "TFCI_MACOS_BAZEL_TEST_DIR_PATH" specifies the directory that Bazel should use # when running tests. Each test will be executed in a separate subdirectory # inside this directory. TF Mac builds need ~150 GB of disk space to be able to # run all the tests. Since TFCI Mac VMs execute Bazel test commands in a # partition with insufficient storage, we specify the
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 15:23:28 GMT 2024 - 6.2K bytes - Viewed (0) -
CONTRIBUTING.md
once you get into the running container so `bazel` can find the `tensorflow` workspace). you can do this by using the following command. As an example- ```bash docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10 ``` Once you have the packages installed, you can run a specific unit test in bazel by doing as follows: ```bash
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configure.py
return int(version_str) def retrieve_bazel_version(): """Retrieve installed bazel version (or bazelisk). Returns: The bazel version detected. """ bazel_executable = which('bazel') if bazel_executable is None: bazel_executable = which('bazelisk') if bazel_executable is None: print('Cannot find bazel. Please install bazel/bazelisk.') sys.exit(1)
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ci/official/envs/disk_cache
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ci/official/utilities/cleanup_summary.sh
} # Print out any ResultStore URLs for Bazel invocations' results. # Each failed target there will have its own representation, making failures # easier to find and read. function resultstore_extract { local \ XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml" python3 \
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ci/official/envs/linux_x86_cuda
# limitations under the License. # ============================================================================== source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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ci/official/README.md
# destroys some temporary bazel data and causes longer builds. # # You will need the NVIDIA Container Toolkit for GPU testing: # https://github.com/NVIDIA/nvidia-container-toolkit # # Note: if you interrupt a bazel command on docker (ctrl-c), you # will need to run `docker exec tf pkill bazel` to quit bazel. # # Note: new files created from the container are owned by "root".
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.gitignore
.DS_Store .ipynb_checkpoints node_modules /.bazelrc.user /.tf_configure.bazelrc /xla_configure.bazelrc /bazel-* /bazel_pip /tools/python_bin_path.sh /tensorflow/tools/git/gen /pip_test /_python_build *.pyc __pycache__ *.swp .vscode/ cmake_build/ tensorflow/contrib/cmake/_build/ .idea/** /build/ [Bb]uild/ /build_output/ /tensorflow/core/util/version_info.cc /tensorflow/python/framework/fast_tensor_util.cpp
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