}).orElse(() -> {
            throwValidationErrorApi(messages -> {
                messages.addErrorsFailedToStartJob(GLOBAL, id);
            });
        });
        return asJson(new ApiResponse().status(Status.OK).result());
    }

    // POST /api/admin/scheduler/{id}/stop
    @Execute(urlPattern = "{}/@word")
    public JsonResponse<ApiResult> post$stop(final String id) {

  op.reset(TFE_NewOp(context.get(), "DestroyResourceOp", status.get()));
  TFE_OpAddInput(op.get(), var_handle, status.get());
  TFE_OpSetDevice(op.get(), name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  num_retvals = 0;
  TFE_Execute(op.get(), nullptr, &num_retvals, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
}

		Rules: []replication.Rule{
			{
				Status:                    replication.Enabled,
				Priority:                  1,
				DeleteMarkerReplication:   replication.DeleteMarkerReplication{Status: replication.Enabled},
				DeleteReplication:         replication.DeleteReplication{Status: replication.Enabled},
				Filter:                    replication.Filter{},

    TF_Status* out_status) const {
  absl::Status status;
  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));
      status = v2_reader_->Lookup(name, out_tensor->get());

};

int64_t LoggedTensorDim(void* data, int dim_index, TF_Status* status) {
  return TFE_TensorHandleDim(reinterpret_cast<LoggedTensor*>(data)->tensor,
                             dim_index, status);
}

int LoggedTensorNumDims(void* data, TF_Status* status) {
  return TFE_TensorHandleNumDims(reinterpret_cast<LoggedTensor*>(data)->tensor,
                                 status);
}

void LoggedTensorDeallocator(void* data) {

            return null;
        })).status(Status.OK).result());
    }

    // PUT /api/admin/fileauth/setting
    @Execute
    public JsonResponse<ApiResult> put$setting(final CreateBody body) {
        validateApi(body, messages -> {});
        if (!isValidFileConfigId(body.fileConfigId)) {
            return asJson(new ApiErrorResponse().message("invalid fileConfigId").status(Status.BAD_REQUEST).result());
        }

                              status);
    CHECK_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

    matmul = TFE_NewOp(ctx, "MatMulFunction", status);
    ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
    TFE_OpAddInput(matmul, h0_task0, status);
    ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

// the error and a nullptr is returned.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_TensorHandleCopySharingTensor(
    TFE_TensorHandle* h, TF_Status* status);

// This function will block till the operation that produces `h` has
// completed. The memory returned might alias the internal memory used by
// TensorFlow. Hence, callers should not mutate this memory (for example by

package replication

import (
	"encoding/xml"
)

// ReplicaModifications specifies if replica modification sync is enabled
type ReplicaModifications struct {
	Status Status `xml:"Status" json:"Status"`
}

// SourceSelectionCriteria - specifies additional source selection criteria in ReplicationConfiguration.
type SourceSelectionCriteria struct {

        return asJson(
                new ApiResult.ApiConfigsResponse<EditBody>().settings(list.stream().map(this::createEditBody).collect(Collectors.toList()))
                        .total(pager.getAllRecordCount()).status(ApiResult.Status.OK).result());
    }

    // GET /api/admin/relatedcontent/setting/{id}
    @Execute
    public JsonResponse<ApiResult> get$setting(final String id) {
        return asJson(