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RELEASE.md
`tf.divide()` is now the recommended division function. `tf.div()` will remain, but its semantics do not respond to Python 3 or `from future` mechanisms. * tf.reverse() now takes indices of axes to be reversed. E.g. `tf.reverse(a, [True, False, True])` must now be written as `tf.reverse(a, [0, 2])`. `tf.reverse_v2()` will remain until 1.0 final. * `tf.mul`, `tf.sub` and `tf.neg` are deprecated in favor of `tf.multiply`, `tf.subtract` and `tf.negative`. *
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.github/workflows/release-branch-cherrypick.yml
with: title: '${{ github.event.inputs.release_branch }} cherry-pick: ${{ steps.cherrypick.outputs.SHORTSHA }} "${{ steps.cherrypick.outputs.TITLE }}"' committer: TensorFlow Release Automation <******@****.***> token: ${{ secrets.JENKINS_TOKEN }} base: ${{ github.event.inputs.release_branch }} branch: ${{ github.event.inputs.release_branch }}-${{ steps.cherrypick.outputs.SHORTSHA }}
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ci/official/requirements_updater/release_updater.sh
do cp ../../../requirements_lock_"$VERSION".txt "requirements_lock_"$VERSION".txt" bazel run \ --experimental_convenience_symlinks=ignore \ --enable_bzlmod=false \ //:requirements_"$VERSION"_release.update sed -i '/^#/d' requirements_lock_"$VERSION".txt mv "requirements_lock_"$VERSION".txt" ../../../requirements_lock_"$VERSION".txt done
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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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tensorflow/c/experimental/filesystem/plugins/gcs/cleanup.h
: released_(src.is_released()), f_(src.release()) {} // Implicitly move-constructible from any compatible Cleanup<G>. // The source will be released as if src.release() were called. // A moved-from Cleanup can be safely destroyed or reassigned. template <typename G> Cleanup(Cleanup<G>&& src) // NOLINT : released_(src.is_released()), f_(src.release()) {}
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tensorflow/c/eager/parallel_device/parallel_device_remote_test.cc
BasicTestsForTwoDevices(context.get(), "/job:worker/replica:0/task:1/device:CPU:0", "/job:worker/replica:0/task:2/device:CPU:0"); worker_server1.release(); worker_server2.release(); } TEST(PARALLEL_DEVICE, TestAsyncCopyOff) { std::unique_ptr<TFE_ContextOptions, decltype(&TFE_DeleteContextOptions)> opts( TFE_NewContextOptions(), TFE_DeleteContextOptions);
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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="${KOKORO_KEYSTORE_DIR}/73361_tensorflow_release_binary_uploader_service_account"
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ci/official/envs/linux_arm64
# limitations under the License. # ============================================================================== TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_arm64_linux" 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"
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tensorflow/c/eager/c_api_unified_experimental.cc
return wrap(t); } void TF_DeleteExecutionContext(TF_ExecutionContext* c) { unwrap(c)->Release(); } TF_AbstractOp* TF_NewAbstractOp(TF_ExecutionContext* c) { return wrap((unwrap(c)->CreateOperation())); } void TF_DeleteAbstractOp(TF_AbstractOp* op) { unwrap(op)->Release(); } void TF_DeleteAbstractTensor(TF_AbstractTensor* t) { unwrap(t)->Unref(); }
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tensorflow/c/c_api.cc
tensorflow::shape_inference::InferenceContext* ic, int num_dims, const int64_t* dims) { if (num_dims != -1) { std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec; dim_vec.reserve(num_dims); for (int i = 0; i < num_dims; ++i) { dim_vec.push_back(ic->MakeDim(dims[i])); } return ic->MakeShape(dim_vec); } else { return ic->UnknownShape(); } }
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