}
  // TODO(b/166669239): This is needed to support AttrBuilder::Get for string
  // attributes. Number type attrs and DataType attrs work fine without this.
  // Consider getting rid of this and making the behavior between number types
  // and string consistent.
  forward_op_->attrs.BuildNodeDef();
  std::unique_ptr<GradientFunction> gradient_fn;
  TF_RETURN_IF_ERROR(registry.Lookup(*forward_op_, &gradient_fn));

    // .backing_device of shape is CPU since the tensor is backed by CPU
    backing_device_name =
        TFE_TensorHandleBackingDeviceName(retvals[0], status.get());
    ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
    ASSERT_TRUE(absl::StrContains(backing_device_name, "CPU:0"))
        << backing_device_name;

    TFE_DeleteOp(shape_op);

#include "tsl/platform/errors.h"

// TODO(b/139060984): After all filesystems are converted, all calls to
// methods from `FileSystem` will have to be replaced to calls to private
// methods here, as part of making this class a singleton and the only way to
// register/use filesystems.

namespace tensorflow {

using UniquePtrTo_TF_Status =
    ::std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)>;

  if (TF_GetCode(status) != TF_OK) return nullptr;
  return new Variable(var_handle, type);
}

void Variable::Destroy(TFE_Context* context, TF_Status* status) {
  // Free the backing buffer for the variable.
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op(
      TFE_NewOp(context, "DestroyResourceOp", status), &TFE_DeleteOp);
  if (TF_GetCode(status) != TF_OK) return;