// inside the `TF_Filesystem_Option_Value` struct)
// as MSVC does not recognize `typeof`.
typedef union TF_Filesystem_Option_Value_Union {
  int64_t int_val;
  double real_val;
  struct {
    char* buf;
    int buf_length;
  } buffer_val;
} TF_Filesystem_Option_Value_Union;

typedef struct TF_Filesystem_Option_Value {
  int type_tag;    // type of values in the values union
  int num_values;  // number of values

    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),

                                                    const char* value,
                                                    TF_Status* status);

// Get configuration key and value using coordination service.
// The config key must be set before getting its value. Getting value of
// non-existing config keys will result in errors.
// If `timeout_in_ms=0`, this call will block until the key-value is set or the
// worker shuts down.

  /// found, call `compute_func`. If `compute_func` set `status` to `TF_OK`,
  /// store a copy of the output parameter in the cache, and another copy in
  /// `value`.
  void LookupOrCompute(const std::string& key, T* value,
                       const ComputeFunc& compute_func, TF_Status* status) {
    if (max_age_ == 0) {
      return compute_func(key, value, status);
    }

    dispatch to logical ops. This brings them more in line with Python and NumPy
    behavior.
*   Adds `tf.SparseTensor.with_values`. This returns a new SparseTensor with the
    same sparsity pattern, but with new provided values. It is similar to the
    `with_values` function of `RaggedTensor`.
*   Adds `StatelessCase` op, and uses it if none of case branches has stateful
    ops.

1.  `envs/*` are lists of variables made with bash syntax. A user must set a
    `TFCI` env param pointing to a list of `env` files.
2.  `utilities/setup.sh`, initialized by all top-level scripts, reads and sets
    values from those `TFCI` paths.
    -   `set -a` / `set -o allexport` exports the variables from `env` files so
        all scripts can use them.
    -   `utilities/setup_docker.sh` creates a container called `tf` with all

    ::testing::Combine(::testing::Values("graphdef"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, GradientCheckerTest,
    ::testing::Combine(::testing::Values("graphdef"),
                       /*tfrt*/ ::testing::Values(false),

  ASSERT_EQ(-1, shape.dim_size(1));
}

INSTANTIATE_TEST_SUITE_P(
    UnifiedCppAPI, UnifiedAPI,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
}  // namespace

  Status SetOption(const std::string& name,
                   const std::vector<string>& values) override;
  Status SetOption(const std::string& name,
                   const std::vector<int64_t>& values) override;
  Status SetOption(const std::string& name,
                   const std::vector<double>& values) override;

 private:
  std::unique_ptr<TF_Filesystem> filesystem_;

TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you
are working with. When loading untrusted checkpoints, the values of the traced
variables from your model are also going to be untrusted. That means that if
your code interacts with the filesystem, network, etc. and uses checkpointed