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ci/official/requirements_updater/requirements.in
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 packaging==23.2
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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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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.cc
switch (block->state) { case FetchState::ERROR: // TF_FALLTHROUGH_INTENDED case FetchState::CREATED: block->state = FetchState::FETCHING; block->mu.Unlock(); // Release the lock while making the API call. block->data.clear(); block->data.resize(block_size_, 0); int64_t bytes_transferred; bytes_transferred = block_fetcher_(key.first, key.second, block_size_,
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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="${KOKORO_KEYSTORE_DIR}/73361_tensorflow_release_binary_uploader_service_account"
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ci/official/utilities/setup_macos.sh
# Pyenv version. We enable this for macOS x86 builds as the default Pyenv on # those VMs does not support installing Python 3.12 and above which we need # for running smoke tests in nightly/release wheel builds. if [[ "${TFCI_MACOS_UPGRADE_PYENV_ENABLE}" == 1 ]]; then # The TFCI Mac VM image seems to have uncommitted local changes to the Pyenv # repository so we have to discard them and reset the working directory before
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ci/official/requirements_updater/README.md
requirements_in = "requirements.in", requirements_txt = "requirements_lock_3_11.txt", ) ``` ``` compile_pip_requirements_3_11( name = "requirements_3_11_release", extra_args = [ "--allow-unsafe", "-P keras-nightly", "-P tb-nightly", ], requirements_in = "requirements.in",
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.bazelrc
test:release_macos_base --build_tests_only --keep_going test:release_macos_base --flaky_test_attempts=3 # Test configs for macOS x86 test:release_macos_x86 --config=release_macos_base # Test configs for macOS Arm64 test:release_macos_arm64 --config=release_macos_base # Ensure release_base is set on windows build:release_cpu_windows --config=release_base # TODO(kanglan): Update windows configs after b/289091160 is fixed
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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/eager/tfe_op_internal.h
// Wraps a pointer to an operation implementation. // // WARNING: Since the underlying object could be ref-counted a user of this // interface cannot destruct the underlying operation object. Instead, call // TFE_DeleteOp who calls Release() on the operation pointer and deletes // the TFE_Op structure. typedef struct TFE_Op TFE_Op; namespace tensorflow { DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation, TFE_Op);
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