==============================================================================*/

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

#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_server_lib.h"

#define TENSORFLOW_C_EAGER_C_API_UNIFIED_EXPERIMENTAL_H_

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"

#ifdef __cplusplus
extern "C" {
#endif

// =============================================================================
// Unified Execution APIs for Eager and tracing backends.
// =============================================================================

#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_remote_test_util.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"

# Where component owners are known, add them here.

/tensorflow/c/eager @qqfish
/tensorflow/core/common_runtime/eager @qqfish
/tenosrflow/core/debug @caisq
/tensorflow/core/kernels/mkl/ @penpornk
/tensorflow/core/kernels/sparse/ @penpornk
/tensorflow/core/nccl/ @azaks2 @chsigg
/tensorflow/python/autograph/ @mdanatg
/tensorflow/python/debug @caisq
/tensorflow/python/eager @rohan100jain
/tensorflow/tools/docs/ @markdaoust

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

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

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

template <typename... LabelType>
int64_t TFE_MonitoringCounterReader::Read(const LabelType&... labels) {
  return counter->Read(labels...);
}

==============================================================================*/
#include "tensorflow/c/eager/gradient_checker.h"

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/tf_status_helper.h"

#define TENSORFLOW_C_EAGER_CUSTOM_DEVICE_TESTUTIL_H_

// A simple logging device to test custom device registration.
#include <memory>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_status.h"

void RegisterLoggingDevice(TFE_Context* context, const char* name,
                           bool strict_scope_placement, bool* arrived_flag,

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

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

#include <cstdint>

#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

/**
 * Interface used to locate the root directory for a given project.
 *
 * The root locator is usually looked up from the plexus container.
 * One notable exception is the computation of the early {@code session.rootDirectory}
 * property which happens very early.  The implementation used in this case
 * will be discovered using the JDK service mechanism.
 *
 * The default implementation will look for a {@code .mvn} child directory

#ifndef TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_
#define TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and
 * parameter specified by `input_index`.