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ci/official/wheel_test/README.md
file for testing, such as: * Ensuring the entire API is importable * Testing downstream projects against the wheel Ensure you have Bazel installed and accessible from your command line. These tests use hermetic Python. They also require a built TensorFlow wheel file and a requirements_lock file. The requirements_lock file is generated by the
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ci/official/envs/rbe
But in .bazelrc, there is no "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX". That setting must exist for this script to function correctly. EOF exit 1 fi TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" # These flags share the user's gcloud credentials with the container, so that bazel
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ci/official/README.md
- Uses `pycpp.sh` - Presubmit jobs (Run on every GitHub PR) - Uses `pycpp.sh`, `code_check_changed_files.sh` These "env" files match up with an environment matrix that roughly covers: - Different Python versions - Linux, MacOS, and Windows machines (these pool definitions are internal) - x86 and arm64 - CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs
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tensorflow/c/experimental/ops/BUILD
load("//tensorflow:tensorflow.default.bzl", "filegroup") load("//tensorflow/core/platform:rules_cc.bzl", "cc_library") # Experimental ops. These will eventually be replaced by machine-generated versions. package( # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"], licenses = ["notice"], ) cc_library( name = "array_ops", srcs = [ "array_ops.cc", ], hdrs = [ "array_ops.h",
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SECURITY.md
TensorFlow supports a wide range of input data formats. For example it can process images, audio, videos, and text. There are several modules specialized in taking those formats, modifying them, and/or converting them to intermediate formats that can be processed by TensorFlow. These modifications and conversions are handled by a variety of libraries that have different security properties and provide different levels of confidence
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ci/official/requirements_updater/requirements.in
wrapt == 1.16.0 tblib == 2.0.0 # Install tensorboard, and keras # Note that here we want the latest version that matches TF major.minor version # Note that we must use nightly here as these are used in nightly jobs # For release jobs, we will pin these on the release branch keras-nightly ~= 3.0.0.dev tb-nightly ~= 2.17.0.a # Test dependencies grpcio >= 1.24.3, < 2.0 portpicker == 1.6.0 scipy == 1.11.3 requests == 2.31.0
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
fi done } @test "No duplicate files on Windows" { cat <<EOF Please rename files so there are no repeats. For example, README.md and Readme.md would be the same file on Windows. In this test, you would get a warning for "readme.md" because it makes everything lowercase. There are repeats of these filename(s) with different casing: EOF find . | tr '[A-Z]' '[a-z]' | sort | uniq -d | tee $BATS_FILE_TMPDIR/repeats
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CONTRIBUTING.md
your response for more than 2 weeks. **4. Approved** - Once the PR is approved, it gets `kokoro:force-run` label applied and it initiates CI/CD tests. - We can't move forward if these tests fail. - In such situations, we may request you to make further changes to your PR for the tests to pass. - Once the tests pass, we now bring all the code into the internal code base,
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ci/official/utilities/code_check_full.bats
fi done } @test "No duplicate files on Windows" { cat <<EOF Please rename files so there are no repeats. For example, README.md and Readme.md would be the same file on Windows. In this test, you would get a warning for "readme.md" because it makes everything lowercase. There are repeats of these filename(s) with different casing: EOF find . | tr '[A-Z]' '[a-z]' | sort | uniq -d | tee $BATS_FILE_TMPDIR/repeats
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ci/official/envs/linux_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64 # Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1
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