query_item)
  if not yes_reply:
    yes_reply = '{} support will be enabled for TensorFlow.'.format(query_item)
  if not no_reply:
    no_reply = 'No {}'.format(yes_reply)

  yes_reply += '\n'
  no_reply += '\n'

  if enabled_by_default:
    question += ' [Y/n]: '
  else:
    question += ' [y/N]: '

  var = environ_cp.get(var_name)
  if var is not None:

      it.second = strings::StrCat(
          "Operation '", op.node.DebugString(), "' was changed by ",
          mutation_type,
          " after it was run by a session. This mutation will have no effect, "
          "and will trigger an error in the future. Either don't modify "
          "nodes after running them or create a new session.");
    }
  }
}

namespace {

  /// been fully persisted.
  ///
  /// DEFAULT IMPLEMENTATION: No op.
  void (*flush)(const TF_WritableFile* file, TF_Status* status);

  /// Syncs contents of `*file` with the filesystem.
  ///
  /// This call should block until filesystem confirms that all buffers have
  /// been flushed and persisted.
  ///
  /// DEFAULT IMPLEMENTATION: No op.
  void (*sync)(const TF_WritableFile* file, TF_Status* status);

        `DynamicLossScale` will no longer affect the weights of the
        LossScaleOptimizer, and vice versa.
    *   The global policy can no longer be set to a non-floating point policy in
        `tf.keras.mixed_precision.experimental.set_policy`
    *   In `Layer.call`, `AutoCastVariable`s will no longer be casted within

  using GradientTape<AbstractTensorHandle, GradientFunction,
                     TapeTensor>::IsPersistent;

  // Adds this tensor to the list of watched tensors.
  //
  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(const AbstractTensorHandle*);

# have Bazelisk pre-installed. "TFCI_MACOS_INSTALL_BAZELISK_URL" contains the
# link to the Bazelisk binary which needs to be downloaded.
if [[ "${TFCI_MACOS_INSTALL_BAZELISK_ENABLE}" == 1 ]]; then
  sudo wget --no-verbose -O "/usr/local/bin/bazel" "${TFCI_MACOS_INSTALL_BAZELISK_URL}"
  chmod +x "/usr/local/bin/bazel"
fi

# "TFCI_MACOS_UPGRADE_PYENV_ENABLE" is used to decide if we need to upgrade the

  # Find all Python py_test targets not tagged "no_pip" or "manual", excluding
  # any targets in ignored packages. Combine this list of targets into a bazel
  # query list (e.g. the list becomes "target+target2+target3")

        plugin_memory_free_(std::move(plugin_memory_free)) {}

  ~ModularFileSystem() override { ops_->cleanup(filesystem_.get()); }

  TF_USE_FILESYSTEM_METHODS_WITH_NO_TRANSACTION_SUPPORT;

  Status NewRandomAccessFile(
      const std::string& fname, TransactionToken* token,
      std::unique_ptr<RandomAccessFile>* result) override;

If the multitenant design allows sharing models, make sure that tenants and
users are aware of the security risks detailed here and that they are going to
be practically running code provided by other users. Currently there are no good
ways to detect malicious models/graphs/checkpoints, so the recommended way to
mitigate the risk in this scenario is to sandbox the model execution.

### Hardware attacks

tf_cuda_cc_test(
    name = "nn_grad_test",
    size = "small",
    srcs = [
        "nn_grad_test.cc",
    ],
    args = ["--heap_check="],  # TODO(b/174752220): Remove
    tags = tf_cuda_tests_tags() + ["no_cuda_asan"],  # b/173654156,
    deps = [
        ":grad_test_helper",
        ":nn_grad",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c/eager:c_api_test_util",