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ci/official/requirements_updater/BUILD.bazel
A. Unique TensorFlower <******@****.***> 1711560469 +0000
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WORKSPACE
# We must initialize hermetic python first. 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/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
test:pip_filters --test_lang_filters=py --flaky_test_attempts=3 --test_size_filters=small,medium test:pip --config=pip_filters -- //bazel_pip/tensorflow/... -//bazel_pip/tensorflow/python/integration_testing/... -//bazel_pip/tensorflow/compiler/tf2tensorrt/... -//bazel_pip/tensorflow/core/tpu/... -//bazel_pip/tensorflow/lite/... -//tensorflow/tools/toolchains/... # For building libtensorflow archives
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
# 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" { bazel build --experimental_cc_shared_library --nobuild --keep_going -- //tensorflow/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/win/... -//tensorflow/tools/toolchains/win_1803/... } teardown_file() { bazel shutdown
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ci/official/requirements_updater/WORKSPACE
# 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/rbe
if ! grep "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" .bazelrc; then cat <<EOF ERROR: RBE was enabled via the 'rbe' env in the 'TFCI' variable. TFCI: $TFCI TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX is "$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX". But in .bazelrc, there is no "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX". That setting must exist for this script to function correctly.
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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 $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10 ``` Once you have the packages installed, you can run a specific unit test in bazel by doing as follows: ```bash
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
test:pip_filters --test_lang_filters=py --flaky_test_attempts=3 --test_size_filters=small,medium test:pip --config=pip_filters -- //bazel_pip/tensorflow/... -//bazel_pip/tensorflow/python/integration_testing/... -//bazel_pip/tensorflow/compiler/tf2tensorrt/... -//bazel_pip/tensorflow/core/tpu/... -//bazel_pip/tensorflow/lite/... -//tensorflow/tools/toolchains/... # For building libtensorflow archives
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ci/official/utilities/cleanup_summary.sh
} # Print out any ResultStore URLs for Bazel invocations' results. # Each failed target there will have its own representation, making failures # easier to find and read. function resultstore_extract { local \ XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml" python3 \
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ci/official/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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