limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_MONITORING_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_MONITORING_INTERNAL_H_

#include <functional>
#include <memory>
#include <string>

#include "absl/memory/memory.h"
#include "tensorflow/core/lib/monitoring/counter.h"

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_CANCELLATION_MANAGER_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_CANCELLATION_MANAGER_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/core/framework/cancellation.h"

struct TFE_CancellationManager;

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_OP_ATTRS_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_OP_ATTRS_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/abstract_op_attrs.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/core/framework/attr_value.pb.h"

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_C_API_MACROS_INTERNAL_H_
#define TENSORFLOW_C_C_API_MACROS_INTERNAL_H_

#ifdef __cplusplus
#include "tensorflow/core/platform/status.h"

// Macro to verify that the field `struct_size` of STRUCT_OBJ is initialized.

#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_GRAD_TEST_HELPER_H_

#include "tensorflow/c/eager/gradients.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {
namespace internal {

void CompareNumericalAndAutodiffGradients(
    Model model, Model grad_model, AbstractContext* ctx,
    absl::Span<AbstractTensorHandle* const> inputs, bool use_function,
    double abs_error = 1e-2);

                           lengths.data(), values.size());
}

namespace internal {
struct AbstractOperationDeleter {
  void operator()(AbstractOperation* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using AbstractOperationPtr =
    std::unique_ptr<AbstractOperation, internal::AbstractOperationDeleter>;

}  // namespace tensorflow

typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(
    const TFE_ContextOptions* opts, TF_Status* status);
TF_CAPI_EXPORT extern void TFE_DeleteContext(TFE_Context* ctx);
TF_CAPI_EXPORT extern TF_DeviceList* TFE_ContextListDevices(TFE_Context* ctx,
                                                            TF_Status* status);

// Clears the internal caches in the TFE context. Useful when reseeding random
// ops.

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_OP_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_OP_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_operation.h"

// Wraps a pointer to an operation implementation.
//

limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_TFE_TENSORHANDLE_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_TENSORHANDLE_INTERNAL_H_

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"

// Wraps a pointer to a tensor handle implementation.
//

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_EAGER_TFE_MONITORING_READER_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_MONITORING_READER_INTERNAL_H_

#include <memory>

#include "tensorflow/core/lib/monitoring/cell_reader.h"

struct TFE_MonitoringCounterReader {
  explicit TFE_MonitoringCounterReader(const char* name) {