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ci/official/wheel_test/README.md
current build. It utilizes the `_api/v2/api_packages.txt` list of packages from the local wheel file specified in the `requirements_lock_<python_version>.txt`. Packages are imported one by one in alphabetical order during runtime. The test doesn't identify package's order-dependent issues; for instance, importing "tf.foo" followed by "tf.bar" won't reveal that "tf.bar" depends on "tf.foo" being imported first.
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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 # test for investigation, you'll need --config=pip_venv instead, and then you
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tensorflow/c/checkpoint_reader.h
std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>, std::unique_ptr<TensorSliceReader::VarToDataTypeMap> > BuildV2VarMaps(); // Invariant: exactly one of "reader_" and "v2_reader_" is non-null. std::unique_ptr<TensorSliceReader> reader_; std::unique_ptr<BundleReader> v2_reader_; std::unique_ptr<TensorSliceReader::VarToShapeMap> var_to_shape_map_;
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tensorflow/c/c_api_test.cc
TF_Graph* graph = TF_NewGraph(); // Make two scalar constants. TF_Operation* one = ScalarConst(1, graph, s, "one"); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); TF_Operation* two = ScalarConst(2, graph, s, "two"); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); // Add oper. TF_Operation* add = Add(one, two, graph, s, "add"); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
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tensorflow/c/eager/c_api_test.cc
TFE_DeleteContext(ctx); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); const int num_devices = TF_DeviceListCount(devices); EXPECT_GE(num_devices, 1) << "At least one CPU device should exist"; for (int i = 0; i < num_devices; ++i) { EXPECT_NE("", TF_DeviceListName(devices, i, status)) << i; EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); }
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ci/official/utilities/rename_and_verify_wheels.sh
# Puts new wheel through auditwheel to rename and verify it, deletes the old # one, checks the filesize, and then ensures the new wheel is installable. set -euxo pipefail cd "$TFCI_OUTPUT_DIR" # Move extra wheel files somewhere out of the way. This script # expects just one wheel file to exist. if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then echo "More than one wheel file is present: moving the oldest to"
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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 # test for investigation, you'll need --config=pip_venv instead, and then you
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CONTRIBUTING.md
airtime before a decision is made regarding whether they are to be migrated to the core. * As every PR requires several CPU/GPU hours of CI testing, we discourage submitting PRs to fix one typo, one warning,etc. We recommend fixing the same issue at the file level at least (e.g.: fix all typos in a file, fix all compiler warnings in a file, etc.) * Tests should follow the
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ci/official/wheel_test/update_requirements.sh
# script to run pip-compile for keras, tensorboard, estimator deps. # if there is a change in requirements.in then all lock files will be updated # accordingly. # -e: abort script if one command fails # -u: error if undefined variable used # -o pipefail: entire command fails if pipe fails. watch out for yes | ... # -o history: record shell history set -euo pipefail -o history # Check for required arguments
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ci/official/containers/linux_arm64/devel.usertools/setup_venv_test.sh
# ============================================================================== 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 # in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the
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