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.

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) {

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

#ifndef TENSORFLOW_C_EAGER_GRADIENTS_INTERNAL_H_
#define TENSORFLOW_C_EAGER_GRADIENTS_INTERNAL_H_

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

namespace tensorflow {
namespace gradients {
namespace internal {

// Helper functions which delegate to `AbstractOperation`, update

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

#include <memory>

#include "tensorflow/core/common_runtime/eager/eager_executor.h"

struct TFE_Executor {
  explicit TFE_Executor(bool async, bool enable_streaming_enqueue,

*   Added `tf.keras.__internal__.KerasTensor`,`tf.keras.__internal__.SparseKerasTensor`, and `tf.keras.__internal__.RaggedKerasTensor` classes. You can use these classes to do instance type checking and type annotations for layer/model inputs and outputs.

    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":tape_operation",
        "//tensorflow/c/eager:abstract_context",
    ],
)

cc_library(
    name = "tape_operation",
    srcs = ["tape_operation.cc"],
    hdrs = [
        "tape_operation.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [

    return ptr->getKind() == kGraph || ptr->getKind() == kMlir;
  }
};

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

using TracingOperationPtr =
    std::unique_ptr<TracingOperation, internal::TracingOperationDeleter>;

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

#include <vector>

#include "tensorflow/core/platform/types.h"

struct TFE_TensorDebugInfo {
  explicit TFE_TensorDebugInfo(const std::vector<int64_t>& dims)

 #  define __hidden_nolink1(local, internal, name, version) \
   __hidden_nolink2 (local, internal, name, version)
 #  define __hidden_nolink2(local, internal, name, version) \
-  extern __typeof (name) internal __attribute__ ((alias (#local))); \
+  extern __typeof (name) internal __attribute__ ((alias (#local)))	\
+    __attribute_copy__ (name);						\
   __hidden_nolink3 (local, internal, #name "@" #version)