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ci/official/wheel_test/README.md
1. Navigates to the `../requirements_updater` directory. 2. Creates a `requirements_wheel_test.in` file and specifies the path to the actual TensorFlow wheel. 3. Creates a `requirements_lock_<python_version>.txt` file. 4. Updates the `requirements_lock_<python_version>.txt` file using a Bazel command. 5. Moves the updated `requirements_lock_<python_version>.txt` file to the `../wheel_test/` directory. ### How it Works in the Presubmit Job
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. # # Pass --config=pip to run the same suite of tests. If you want to run just one
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tensorflow/c/experimental/filesystem/modular_filesystem.cc
stat->length = stats.length; stat->mtime_nsec = stats.mtime_nsec; stat->is_directory = stats.is_directory; } return StatusFromTF_Status(plugin_status.get()); } Status ModularFileSystem::IsDirectory(const std::string& name, TransactionToken* token) { if (ops_->is_directory == nullptr) return FileSystem::IsDirectory(name, token);
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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
s = fs->CreateDir(root_dir_); if (!s.ok()) { GTEST_SKIP() << "Cannot create working directory: " << s; } } // Converts path reference to URI reference. // // If URI scheme is empty, URI reference is `path` relative to current test // root directory. Otherwise, we need to add the `<scheme>://` in front of // this path. //
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ci/official/utilities/code_check_changed_files.bats
setup_file() { bazel version # Start the bazel server # Fixes "fatal: detected dubious ownership in repository" for Docker. git config --system --add safe.directory '*' git config --system protocol.file.allow always # Note that you could generate a list of all the affected targets with e.g.: # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. # # Pass --config=pip to run the same suite of tests. If you want to run just one
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ci/official/requirements_updater/updater.sh
# script to run pip-compile for each requirement. # if there is a change in requirements.in then all lock files will be updated # accordingly # All commands run relative to this directory cd "$(dirname "${BASH_SOURCE[0]}")" mv BUILD.bazel BUILD SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12") for VERSION in "${SUPPORTED_VERSIONS[@]}" do touch "requirements_lock_$VERSION.txt"
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ci/official/containers/linux_arm64/devel.usertools/setup_venv_test.sh
# limitations under the License. # ============================================================================== set -euxo pipefail # Run this from inside the tensorflow github directory. # Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file" # Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl" # # This will create a venv with that wheel file installed in it, and a symlink
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ci/official/envs/versions_upload
# Release jobs are very basic. They don't use any caching or RBE, # but they do upload logs to resultstore. # IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to # pretend the path is a directory. TFCI_ARTIFACT_FINAL_GCS_ENABLE=1 TFCI_ARTIFACT_FINAL_GCS_SA_PATH="${KOKORO_KEYSTORE_DIR}/73361_tensorflow_release_binary_uploader_service_account" TFCI_ARTIFACT_FINAL_GCS_URI="gs://tensorflow/versions/"
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tensorflow/api_template.__init__.py
_os.environ["TF2_BEHAVIOR"] = "1" from tensorflow.python import tf2 as _tf2 _tf2.enable() # API IMPORTS PLACEHOLDER # WRAPPER_PLACEHOLDER # Make sure directory containing top level submodules is in # the __path__ so that "from tensorflow.foo import bar" works. # We're using bitwise, but there's nothing special about that. _API_MODULE = _sys.modules[__name__].bitwise
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