See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"

#include "tensorflow/c/eager/gradient_checker.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace gradients {

  private volatile int remaining;

  private static final AtomicHelper ATOMIC_HELPER;

  private static final LazyLogger log = new LazyLogger(AggregateFutureState.class);

  static {
    AtomicHelper helper;
    Throwable thrownReflectionFailure = null;
    try {
      helper =
          new SafeAtomicHelper(
              newUpdater(AggregateFutureState.class, Set.class, "seenExceptions"),

Chef <******@****.***> 1709605377 +0700

Jinzhu <******@****.***> 1710820228 +0800

Mathieu Parent <******@****.***> 1692455951 +0200

#ifndef TENSORFLOW_C_CHECKPOINT_READER_H_
#define TENSORFLOW_C_CHECKPOINT_READER_H_

#include <memory>
#include <string>

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"

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opencmit2 <******@****.***> 1702424612 +0800

  virtual std::vector<tensorflow::Device*> ListAllTfDevices() = 0;

  //===--------------------------------------------------------------------===//
  // Following are helper functions to assist integrating TFRT with current
  // TF eager runtime.
  // TODO(b/172877902): These helper functions are currently used to support
  // PyFuncOp on TFRT, and might be useful for ops that directly use low

### Typannotationen und Tooling

Sehen wir uns zunächst an, wie Editor, mypy und andere Tools dies sehen würden.

`BaseUser` verfügt über die Basis-Felder. Dann erbt `UserIn` von `BaseUser` und fügt das Feld `Passwort` hinzu, sodass dass es nun alle Felder beider Modelle hat.

Wir annotieren den Funktionsrückgabetyp als `BaseUser`, geben aber tatsächlich eine `UserIn`-Instanz zurück.