const = 0;
  virtual Status SetInput(size_t index,
                          ImmediateExecutionTensorHandle* input) = 0;

  virtual ImmediateExecutionContext* GetContext() const = 0;

  // Following two methods are used to support custom device.
  // Return true if the inputs contain custom device tensor handle. It means
  // that the argument need to be handled by a custom device.

TF_CAPI_EXPORT extern TF_SessionOptions* TF_NewSessionOptions(void);

// Set the target in TF_SessionOptions.options.
// target can be empty, a single entry, or a comma separated list of entries.
// Each entry is in one of the following formats :
// "local"
// ip:port
// host:port
TF_CAPI_EXPORT extern void TF_SetTarget(TF_SessionOptions* options,
                                        const char* target);

    TF_ShapeAndTypeList** shape_list_array, int num_items);

// Infer shapes for the given `op`. The arguments mimic the arguments of the
// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the

  virtual int64_t TensorId(Gradient* tensor) const = 0;

  // Converts a Gradient to a TapeTensor.
  virtual TapeTensor TapeTensorFromGradient(Gradient* gradient) const = 0;

  // Marks the following gradient as a result so it's not consumed by backward
  // functions.
  virtual void MarkAsResult(Gradient* gradient) const = 0;

  // Deletes the input tensor.

  virtual void ResetGlobalRendezvousForFunction() = 0;

  //===--------------------------------------------------------------------===//
  // Following are features in current TF Eager Runtime.
  // TODO(tfrt-devs): Figure out a way to deprecate following features after
  // migrated to TFRT.
  //===--------------------------------------------------------------------===//

// workers name). Operations created in this context can then be executed on
// any of these remote workers by setting an appropriate device.
//
// If the following is set, all servers identified by the
// ServerDef must be up when the context is created.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDef(TFE_Context* ctx,

#ifdef __cplusplus
extern "C" {
#endif  // __cplusplus

/// SECTION 1. Opaque data structures to hold plugin specific data
/// ----------------------------------------------------------------------------
///
/// The following data structures incorporate a `void*` that is opaque to
/// TensorFlow but can be used by each filesystem plugin to represent internal
/// data.
///
/// We prefer to have these structures instead of passing `void*` into

                                   absl::Span<AbstractTensorHandle*>)>;

// Runs `model` maybe wrapped in a function call op. This can be thought as
// being equivalent to the following python code.
//
// if use_function:
//   outputs = tf.function(model)(inputs)
// else:
//   outputs = model(inputs)
Status RunModel(Model model, AbstractContext* ctx,