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ci/official/wheel_test/README.md
The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2 init files creation process and is subsequently stored in the wheel file after the build. It also contains a few paths that cannot be directly imported. These paths point to attributes or sub-modules within a module's namespace, but they don't correspond to an actual file or directory on the filesystem. The list of
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ci/official/utilities/code_check_changed_files.bats
# limitations under the License. # ============================================================================== 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.:
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tensorflow/c/c_api_internal.h
TF_GUARDED_BY(mu); // The keys of this map are all the active sessions using this graph. Each // value records whether the graph has been mutated since the corresponding // session has been run (this is detected in RecordMutation function). If the // string is empty, no mutation has occurred. Otherwise the string is a // description of the mutation suitable for returning to the user. //
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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
#include "tensorflow/core/platform/test.h" #include "tensorflow/core/util/command_line_flags.h" #if defined(PLATFORM_WINDOWS) // Make mkdir resolve to _mkdir to create the test temporary directory. #include <direct.h> #define mkdir(name, mode) _mkdir(name) // Windows defines the following macros to convert foo to fooA or fooW, // depending on the type of the string argument. We don't use these macros, so // undefine them here.
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CONTRIBUTING.md
may exist in your changes. #### Running unit tests There are two ways to run TensorFlow unit tests. 1. Using tools and libraries installed directly on your system. Refer to the [CPU-only developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-cpu.Dockerfile) and
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tensorflow/c/experimental/filesystem/plugins/gcs/cleanup.h
// while (ReadDataObject(fp, &d)) { // if (d.IsBad()) { // LOG(ERROR) << "Bad Data"; // return; // } // PushGoodData(d); // } // } // // You can use Cleanup<F> directly, instead of using MakeCleanup and auto, // but there's rarely a reason to do that. // // You can call 'release()' on a Cleanup object to cancel the cleanup.
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CODE_OF_CONDUCT.md
If you are experiencing or witnessing conflict, we ask you to use the following escalation strategy to address the conflict: 1. Address the perceived conflict directly with those involved, preferably in a real-time medium. 2. If this fails, get a third party (e.g. a mutual friend, and/or someone with background on the issue, but not involved in the conflict) to intercede.
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tensorflow/c/eager/abstract_operation.h
// Release any underlying resources, including the interface object. // // WARNING: The destructor of this class is marked as protected to disallow // clients from directly destroying this object since it may manage it's own // lifetime through ref counting. Thus this must be allocated on the heap and // clients MUST call Release() in order to destroy an instance of this class.
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
Here are the affected tests: EOF while read dep; do echo "For dependency $dep:" # For every missing dependency, find the tests which directly depend on # it, and print that list for debugging. Not really clear if this is # helpful since the only examples I've seen are enormous. bazel query "rdeps(kind(py_test, $(cat $BATS_TEST_TMPDIR/deps)), $dep, 1)"
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tensorflow/c/BUILD
"//tensorflow/core:array_ops_op_lib", "//tensorflow/core:bitwise_ops_op_lib", "//tensorflow/core:control_flow_ops_op_lib", "//tensorflow/core:core_cpu_internal", "//tensorflow/core:direct_session", "//tensorflow/core:framework", "//tensorflow/core:framework_internal", "//tensorflow/core:functional_ops_op_lib", "//tensorflow/core:lib",
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