int version = TFE_CUSTOM_DEVICE_VERSION;
  // Method to copy a tensor to the custom device.
  TFE_TensorHandle* (*copy_tensor_to_device)(TFE_Context* context,
                                             TFE_TensorHandle* tensor,
                                             TF_Status* status,
                                             void* device_info);

  // Method to copy a tensor from the custom device to a target device.

#include <memory>

#include "absl/types/optional.h"
#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_operation.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"
#include "tensorflow/c/tensor_interface.h"
#include "tensorflow/core/framework/cancellation.h"
#include "tensorflow/core/framework/device_attributes.pb.h"
#include "tensorflow/core/framework/op_def.pb.h"

// This may cause incorrectness in graph analyses, but is useful for simulation
// or scheduling.
// If include_input_tensor_values is true, the values of constant
// tensors will included in the input properties.
// If include_output_tensor_values is true, the values of constant tensors will
// be included in the output properties.
TF_CAPI_EXPORT extern void TF_InferStatically(

#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value);

// Return a tensor handle containing a int scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, int value);

// Return a tensor handle containing a bool scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, bool value);

                                                       TF_Status* status) const;

  // Construct a parallel tensor consisting of the scalar values from `values`.
  template <typename DataType>
  std::unique_ptr<ParallelTensor> ScalarsFromSequence(
      absl::Span<const DataType> values, TFE_Context* context,
      TF_Status* status) const;

                                                     TF_Tensor** value,
                                                     TF_Status* status);

// Fills in `values` with the TF_Tensor values of the attribute `attr_name` of
// `oper`. `values` must point to an array of TF_Tensor* of length at least
// `max_values` (ideally set to TF_AttrMetadata.list_size from

void GradientTape<Gradient, BackwardFunction, TapeTensor>::DeleteTrace(
    int64_t tensor_id) {
  auto it = tensor_usage_.find(tensor_id);
  if (it == tensor_usage_.end()) {
    return;
  }
  it->second--;
  if (it->second != 0) {
    return;
  }
  tensor_usage_.erase(it);
  auto tensor_op_it = tensor_tape_.find(tensor_id);
  if (tensor_op_it == tensor_tape_.end()) {
    return;
  }

TF_CAPI_EXPORT extern TF_Tensor* TF_DequeueNamedTensor(TF_Session* session,
                                                       int tensor_id,
                                                       TF_Status* status);

// On success, enqueues `tensor` into a TF-managed FifoQueue given by
// `tensor_id`, associated with `session`. There must be a graph node named
// "fifo_queue_enqueue_<tensor_id>", to be executed by this API call. It reads

#include "tensorflow/c/eager/tfe_monitoring_internal.h"  // IWYU pragma: export
#include "tensorflow/c/eager/tfe_op_attrs_internal.h"  // IWYU pragma: export
#include "tensorflow/c/eager/tfe_tensor_debug_info_internal.h"  // IWYU pragma: export

// TODO(b/154564140): Move this to its own header. This requires splitting
// c_api_experimental.h
struct TFE_ContextOptions {
  TF_SessionOptions session_options;

                                                   size_t proto_len,
                                                   TF_Status* status);

// A handle to a tensor on a device.
//
// Like a TF_Tensor, a TFE_TensorHandle refers to a tensor with a value, shape,
// type etc. Unlike a TF_Tensor, a TFE_TensorHandle may refer to such tensors
// placed in the memory of different devices or remote address spaces.