#include "tensorflow/c/kernels.h"
#include "tensorflow/c/kernels_experimental.h"
#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/c/tf_tensor_internal.h"
#include "tensorflow/compiler/jit/variable_info.h"
#include "tensorflow/compiler/jit/variable_info_util.h"
#include "xla/pjrt/c/pjrt_c_api.h"

#include "tensorflow/c/eager/tfe_op_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"
#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_server_lib.h"

  %0 = corert.executeop(%cpu) "tf.Relu"(%arg0) { T = f32 } : 1
  %arg1 = tfrt_fallback_async.corert_tensorhandle_to_fallback_tensor %arg1_th {_tfrt_cost = 1 : i64, device = "/CPU:0"} : (!corert.tensorhandle) -> (!tfrt_fallback.tf_tensor)
  %1 = tfrt_fallback_async.executeop key(0) cost(100) device("/CPU:0") "tf.Relu"(%arg1) { T = f32 } : 1
  tfrt.return

};

// The MLIR type represents a tensorflow::Tensor.
class TFTensorType : public Type::TypeBase<TFTensorType, Type, TypeStorage> {
 public:
  using Base::Base;
  static constexpr StringLiteral name = "tfrt.tf_tensor";
};

// The MLIR type represents a tensorflow::Allocator.
class TFAllocatorType
    : public Type::TypeBase<TFAllocatorType, Type, TypeStorage> {
 public:
  using Base::Base;

}  // namespace tensorflow

static void TF_Run_Setup(int noutputs, TF_Tensor** c_outputs,
                         TF_Status* status) {
  status->status = absl::OkStatus();
  for (int i = 0; i < noutputs; ++i) {
    c_outputs[i] = nullptr;
  }
}

// TF_TensorToTensorV1 decodes a string serialization to DT_RESOURCE.
// In the TFv1 convention, TF_Tensor can hold a string serialization of

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

#include "tensorflow/c/safe_ptr.h"

namespace tensorflow {

Safe_TF_TensorPtr make_safe(TF_Tensor* tensor) {
  return Safe_TF_TensorPtr(tensor);
}

Safe_TFE_TensorHandlePtr make_safe(TFE_TensorHandle* handle) {
  return Safe_TFE_TensorHandlePtr(handle);
}

Safe_TF_StatusPtr make_safe(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.
typedef struct TFE_TensorHandle TFE_TensorHandle;

TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandle(const TF_Tensor* t,

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/test.h"

using tensorflow::Status;

==============================================================================*/
#ifndef TENSORFLOW_C_TF_TSTRING_H_
#define TENSORFLOW_C_TF_TSTRING_H_

#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/ctstring.h"

#ifdef __cplusplus
extern "C" {
#endif

TF_CAPI_EXPORT extern void TF_StringInit(TF_TString *t);

                                                     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