// capture some inputs and then add a node in the graph. The output tensors are
// returned through the provided TF_OutputList.
// Any active tape will observe the effects of this execution.
void TF_ExecuteOperation(TF_AbstractOp* op, int num_inputs,
                         TF_AbstractTensor* const* inputs, TF_OutputList* o,
                         TF_Status* s);

class ImmediateExecutionContext;
class AbstractOpAttrs;

// Abstract interface to an operation.
class ImmediateExecutionOperation : public AbstractOperation {
 public:
  virtual void Clear() = 0;

  // Returns the inputs of this op.
  virtual absl::Span<ImmediateExecutionTensorHandle* const> GetInputs()
      const = 0;
  virtual Status SetInput(size_t index,
                          ImmediateExecutionTensorHandle* input) = 0;

                            void* device_info) = nullptr;

  // Pins the op to `device` based on inputs to `op`. Returns true
  // signifying to pin to the current custom device. Returns false
  // to pin to the physical device.
  //
  // This function is guaranteed to be called only when all of the custom-device
  // inputs are on this device.
  bool (*shall_pin_to_this_device)(const TFE_Op* op, TF_Status* s) = nullptr;

  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(int64_t tensor_id);

  // Records an operation with inputs `input_tensor_id` and outputs
  // `output_tensors` on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has trainable dtype.
  //

// 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
//     op for shape inference.

                                              TFE_TensorHandle** inputs,
                                              int num_inputs,
                                              TF_Status* status);

// Fetches the current number of inputs attached to `op`.
//
// Does not use the operation's definition to determine how many inputs should
// be attached. It is intended for use with TFE_OpGetFlatInput to inspect an

  virtual Status SetDeviceName(const char* name) = 0;

  virtual Status AddInput(AbstractTensorHandle* input) = 0;
  virtual Status AddInputList(
      absl::Span<AbstractTensorHandle* const> inputs) = 0;
  virtual Status Execute(absl::Span<AbstractTensorHandle*> retvals,
                         int* num_retvals) = 0;

  virtual Status SetAttrString(const char* attr_name, const char* data,

//  public:
//   Status Compute(Context* ctx,
//                  absl::Span<AbstractTensorHandle* const> grad_inputs,
//                  absl::Span<AbstractTensorHandle*> grad_outputs) override {
//     grad_outputs[0] = grad_inputs[0];
//     grad_outputs[1] = grad_inputs[0];
//     grad_outputs[0]->Ref();
//     grad_outputs[1]->Ref();
//     return OkStatus();
//   }
//   ~AddGradientFunction() override {}

Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

// Records the inputs in the `ForwardOperation`.
Status AddInput(AbstractOperation*, AbstractTensorHandle*, ForwardOperation*);
Status AddInputList(AbstractOperation*,
                    absl::Span<AbstractTensorHandle* const> inputs,
                    ForwardOperation*);

// Sets the attrs in the `ForwardOperation`.

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,
                             absl::Span<AbstractTensorHandle* const> inputs,
                             std::vector<AbstractTensorHandle*>* params);

// A callable that takes tensor inputs and returns zero or more tensor outputs.
using Model = std::function<Status(AbstractContext*,