#define TP_OPTIMIZER_REGISTRATION_PARAMS_STRUCT_SIZE \
  TF_OFFSET_OF_END(TP_OptimizerRegistrationParams, optimizer)

// TF_InitGraph is used to do graph optimizer registration.
// Plugin should implement TF_InitGraph to register graph optimizers.
void TF_InitGraph(TP_OptimizerRegistrationParams* params, TF_Status* status);

// Get a set of node names that must be preserved. They can not be transformed

// scope for now. I'm just mentioning this here as that transition will mean
// removal of the registration part from `Env` and adding it here instead: we
// will need tables to hold for each scheme the function tables that implement
// the needed functionality instead of the current `FileSystemRegistry` code in
// `core/platform/env.cc`.
class ModularFileSystem final : public FileSystem {
 public:
  ModularFileSystem(

unauthorized access to data or models, but also to prevent malicious users or
tenants sending graphs to execute under another tenant’s identity.

The isolation mechanisms are the responsibility of the users to design and
implement, and therefore security issues deriving from their absence are not
considered a vulnerability in TensorFlow.

### Resource allocation

A denial of service caused by one model could bring down the entire server, but

/// plugins (see initial RFC https://github.com/tensorflow/community/pull/101).
///
/// Both core TensorFlow and every plugin will use this header. The associated
/// `.cc` file is only used by core TensorFlow to implement checking needed for
/// plugin registration and ensuring API and ABI compatibility. Plugin authors
/// don't need to read the `.cc` file but they should consult every section of

  }
  const string& Name() const override { return op_type_; }
  const string& DeviceName() const override { return device_name_; }

  Status SetDeviceName(const char* name) override {
    // TODO(srbs): Implement this.
    device_name_ = name;
    return absl::OkStatus();
  }

  Status AddInput(AbstractTensorHandle* input) override {
    GraphTensor* t = dyn_cast<GraphTensor>(input);
    if (!t) {

  }

 private:
  TFE_Context* context_;
  TFE_CustomDevice device_;
  void* info_;
  string name_;
};

// An adapter which wraps the shape/data produced by C custom devices and uses
// it to implement custom device methods.
class CAPICustomDeviceTensorHandle
    : public tensorflow::CustomDeviceTensorHandle {
 public:
  CAPICustomDeviceTensorHandle(tensorflow::ImmediateExecutionContext* context,

          bucket.c_str(), object.c_str(), stat->base.length,
          stat->generation_number, stat->base.mtime_nsec);
  return TF_SetStatus(status, TF_OK, "");
}

// TODO(vnvo2409): Implement later
void NewRandomAccessFile(const TF_Filesystem* filesystem, const char* path,
                         TF_RandomAccessFile* file, TF_Status* status) {
  std::string bucket, object;

        Protocol available through
        `tf.types.experimental.SupportsTracingProtocol`.
    *   `TypeSpec` classes (as associated with `ExtensionTypes`) also implement
        the Tracing Protocol which can be overridden if necessary.
    *   The newly introduced `reduce_retracing` option also uses the Tracing
        Protocol to proactively generate generalized traces similar to

  //
  // For example some tensor handles may represent distributed values, in which
  // case placement information is lost when resolving the handle.
  //
  // If false, a caller might implement pretty-printing by resolving and
  // iterating over the resulting tensor. This may still be viable if resolving
  // the handle loses information, but `SummarizeValue` would be more precise.

// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if
// `ranks[i] == 1`, then `shapes[i]` may be nullptr.
//
// TODO(akshayka): Implement a corresponding getter method.
void TF_GraphSetOutputHandleShapesAndTypes(TF_Graph* graph, TF_Output output,
                                           int num_shapes_and_types,