==============================================================================*/
#include "tensorflow/c/eager/tracing_utils.h"

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/experimental/gradients/tape/tape_operation.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

namespace tensorflow {
namespace tracing {

    input_ids[i] = ToId(inputs[i]);
    input_dtypes[i] = inputs[i]->DataType();
  }
  std::vector<TapeTensor> tape_tensors;
  tape_tensors.reserve(outputs.size());
  for (auto t : outputs) {
    tape_tensors.push_back(TapeTensor(t));
  }
  GradientTape::RecordOperation(
      op_name, tape_tensors, input_ids, input_dtypes,
      [gradient_function]() -> GradientFunction* { return gradient_function; },

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/tensor_float_32_utils.h"
#include "tensorflow/core/platform/test.h"

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/tensor_float_32_utils.h"
#include "tensorflow/core/platform/test.h"

    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":abstract_operation",
        ":c_api_unified_internal",
        "//tensorflow/c/experimental/gradients/tape:tape_operation",
        "//tensorflow/core/lib/llvm_rtti",
        "//tensorflow/core/platform:errors",
    ],
)

cc_library(
    name = "gradients_internal",
    srcs = [
        "gradients.cc",

running models or processes in the same system. GPUs can also have
implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

## Reporting vulnerabilities

### Vulnerabilities in TensorFlow

	ModTime time.Time `msg:"mt"`

	// Total file size.
	Size int64 `msg:"sz"`

	// File mode bits.
	Mode uint32 `msg:"m"`

	// WrittenByVersion is the unix time stamp of the MinIO
	// version that created this version of the object.
	WrittenByVersion uint64 `msg:"wv"`

	// File metadata
	Metadata map[string]string `msg:"meta"`

	// All the parts per object.

  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.LabelSelector selector = 2;

  // template is the object that describes the pod that will be created if
  // insufficient replicas are detected. Each pod stamped out by the StatefulSet
  // will fulfill this Template, but have a unique identity from the rest
  // of the StatefulSet. Each pod will be named with the format

Disons que vous voulez ajouter des traductions pour le Créole, et que ce n'est pas encore dans les documents.

En vérifiant le lien ci-dessus, le code pour "Créole" est `ht`.

L'étape suivante consiste à exécuter le script pour générer un nouveau répertoire de traduction :

<div class="termy">

```console
// Use the command new-lang, pass the language code as a CLI argument

Pour finir vous allez au comptoir 🔀, vers la tâche initiale qui est désormais terminée ⏯, récupérez les burgers 🍔, remerciez le serveur et ramenez les burgers 🍔 à votre table. Ceci termine l'étape / la tâche d'interaction avec le comptoir ⏹. Ce qui ensuite, crée une nouvelle tâche de "manger les burgers"  🔀 ⏯, mais la précédente, "récupérer les burgers" est terminée ⏹.

#### Burgers parallèles