//
  // 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.
  virtual void Release() = 0;

  virtual Status Reset(const char* op, const char* raw_device_name) = 0;

// `underlying_devices` and `b` on the second. Running `a_unpacked, b_unpacked =
// TPUReplicatedOutput(input=x, num_replicas=2)` un-packs the parallel tensor
// into its components.
//
// The filled `device` struct and the allocated `device_info` struct may be
// passed to TFE_RegisterCustomDevice. The `device_name` arguments must match.
void AllocateParallelDevice(const char* device_name,
                            const char* const* underlying_devices,

    TF_CoordinationServiceAgent* agent, TF_Status* status);

// Obtains key-value from coordination service agent. The returned `TF_Buffer`
// is a newly allocated buffer to hold the string key-value, and caller is
// responsible for managing the lifetime. If error, `status` will be set and a
// nullptr will be returned.
TF_CAPI_EXPORT extern TF_Buffer* TF_CoordinationServiceGetKeyValue(

  ops->scheme = strdup(uri);
}

void TF_InitPlugin(TF_FilesystemPluginInfo* info) {
  info->plugin_memory_allocate = plugin_memory_allocate;
  info->plugin_memory_free = plugin_memory_free;
  info->num_schemes = 2;
  info->ops = static_cast<TF_FilesystemPluginOps*>(
      plugin_memory_allocate(info->num_schemes * sizeof(info->ops[0])));
  ProvideFilesystemSupportFor(&info->ops[0], "");

TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces

for an example.

See
[this commit](https://github.com/tensorflow/tensorflow/commit/5f7f05a80aac9b01325a78ec3fcff0dbedb1cc23)
as a rough example of the steps below.

All the files referenced below are located in the same directory as this README,
unless indicated otherwise.

1) Add the new version to the `VERSIONS` variable inside
   `tensorflow/tools/toolchains/python/python_repo.bzl`. \

        read_only_memory_region_ops_(std::move(read_only_memory_region_ops)),
        plugin_memory_allocate_(std::move(plugin_memory_allocate)),
        plugin_memory_free_(std::move(plugin_memory_free)) {}

  ~ModularFileSystem() override { ops_->cleanup(filesystem_.get()); }

  TF_USE_FILESYSTEM_METHODS_WITH_NO_TRANSACTION_SUPPORT;

  Status NewRandomAccessFile(

  return new PJRT_Buffer{std::move(*buffer), c_api_client->pjrt_c_client()};
}

TEST(TensorPjRtBufferUtilTest, GetPjRtCBufferFromTensorNoBuffer) {
  auto allocator = std::make_unique<AsyncValueAllocator>();
  tensorflow::Tensor tensor(allocator.get(), DT_FLOAT, {1});

  EXPECT_THAT(
      GetPjRtCBufferFromTensor(&tensor),
      StatusIs(error::INTERNAL, HasSubstr(absl::StrCat(

// \brief Get a pointer to a symbol from a dynamic library.
//
// "handle" should be a pointer returned from a previous call to
// TF_LoadLibraryFromEnv. On success, place OK in status and return a pointer to
// the located symbol. Otherwise returns nullptr and set error status.
TF_CAPI_EXPORT extern void* TF_GetSymbolFromLibrary(void* handle,
                                                    const char* symbol_name,