TF_Status* status) const {
  if (op_ == nullptr) {
    TFE_ContextSetExecutorForThread(context, executor_.get());
    op_.reset(TFE_NewOp(context, operation_name, status));
    if (TF_GetCode(status) != TF_OK) return;
    TFE_OpSetDevice(op_.get(), device_.c_str(), status);
    if (TF_GetCode(status) != TF_OK) return;
  } else {

        TFE_NewOp(context, "Const", status), TFE_DeleteOp);
    if (TF_GetCode(status) != TF_OK) return nullptr;
    TFE_OpSetDevice(const_op.get(), underlying_devices_[device_index].c_str(),
                    status);
    if (TF_GetCode(status) != TF_OK) return nullptr;
    TFE_OpSetAttrTensor(const_op.get(), "value", tensor.get(), status);
    if (TF_GetCode(status) != TF_OK) return nullptr;

  ASSERT_EQ(0, TFE_TensorDebugInfoOnDeviceNumDims(debug_info));

  TFE_DeleteTensorDebugInfo(debug_info);
  TFE_DeleteTensorHandle(h);
  TFE_DeleteContext(ctx);
  TF_DeleteStatus(status);
}

TEST(CApiDebug, 2DCPU) {
  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  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());
}

        }).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) {

    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());

                              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 {

	"bytes"
	"encoding/xml"
)

// Status represents Enabled/Disabled status
type Status string

// Supported status types
const (
	Enabled  Status = "Enabled"
	Disabled Status = "Disabled"
)

// DeleteMarkerReplication - whether delete markers are replicated - https://docs.aws.amazon.com/AmazonS3/latest/dev/replication-add-config.html
type DeleteMarkerReplication struct {