// TFE_DeleteOp who calls Release() on the operation pointer and deletes
// the TFE_Op structure.
typedef struct TFE_Op TFE_Op;

namespace tensorflow {

DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation, TFE_Op);
DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation*, TFE_Op*);

}  // namespace tensorflow

// the TFE_TensorHandle structure.
typedef struct TFE_TensorHandle TFE_TensorHandle;

namespace tensorflow {

DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionTensorHandle,
                            TFE_TensorHandle);
DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionTensorHandle*,
                            TFE_TensorHandle*);

}  // namespace tensorflow

// --------------------------------------------------------------------------
// C API for Graph. The API is under active development and eventually
// should allow registering a plugin graph optimizer with TensorFlow.
//
// Conventions:
//   * Struct prefix indicates whether struct fields should be filled by the
//     plugin or core implementation:
//     * Struct that should be filled by the plugin: `TP_OptimizerConfigs`,

    int64_t init_timeout_in_ms, TF_Status* status,
    bool clear_existing_contexts);

// Set server def with retries and timeout. This is helpful for fault-tolerant
// initial connection in high-preemption environments, such as
// ParameterServerStrategy training.
// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeoutAndRetries(

// C API for TensorFlow.
//
// The API leans towards simplicity and uniformity instead of convenience
// since most usage will be by language specific wrappers.
//
// Conventions:
// * We use the prefix TF_ for everything in the API.
// * Objects are always passed around as pointers to opaque structs
//   and these structs are allocated/deallocated via the API.

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

#ifndef TENSORFLOW_C_CONVERSION_MACROS_H_
#define TENSORFLOW_C_CONVERSION_MACROS_H_

#define DEFINE_CONVERSION_FUNCTIONS(cpp_impl, wrapper)                         \
  inline cpp_impl *unwrap(wrapper *w) {                                        \

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

struct TFE_CancellationManager;
typedef struct TFE_CancellationManager TFE_CancellationManager;

namespace tensorflow {
DEFINE_CONVERSION_FUNCTIONS(tensorflow::CancellationManager,
                            TFE_CancellationManager);
DEFINE_CONVERSION_FUNCTIONS(tensorflow::CancellationManager*,

==============================================================================*/
#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"

TF_CAPI_EXPORT extern void TFE_ContextEndStep(TFE_Context* ctx);

#ifdef __cplusplus
} /* end extern "C" */
#endif

#ifdef __cplusplus
// A workaround to ease conversion to and from numpy objects and
// TFE_TensorHandle's.
//
// TODO(ashankar): Figure out an alternative scheme that precludes the need for
// these API-boundary breaking methods.
namespace tensorflow {
class Tensor;

}  // namespace tracing

DEFINE_CONVERSION_FUNCTIONS(AbstractContext, TF_ExecutionContext)
DEFINE_CONVERSION_FUNCTIONS(AbstractTensorHandle, TF_AbstractTensor)
DEFINE_CONVERSION_FUNCTIONS(AbstractFunction, TF_AbstractFunction)
DEFINE_CONVERSION_FUNCTIONS(AbstractOperation, TF_AbstractOp)
DEFINE_CONVERSION_FUNCTIONS(OutputList, TF_OutputList)
}  // namespace tensorflow