TFE_CancelCallback callback1;
  callback1.callback = [](void* context) {
    ADD_FAILURE() << "Callback1 should be deregistered.";
  };
  TFE_CancellationToken token1 = TFE_CancellationManagerGetToken(c_mgr);
  EXPECT_TRUE(TFE_CancellationManagerRegisterCallback(c_mgr, token1, &callback1,
                                                      "callback1"));

  TFE_CancelCallback callback2;

                                   TF_Status* status) {
  bool downloaded_block = false;
  auto reconcile_state = MakeCleanup([this, &downloaded_block, &key, &block] {
    // Perform this action in a cleanup callback to avoid locking mu_ after
    // locking block->mu.
    if (downloaded_block) {
      absl::MutexLock l(&mu_);
      // Do not update state if the block is already to be evicted.
      if (block->timestamp != 0) {

  cat > $BATS_TEST_TMPDIR/ignore_deps_for_these_packages <<EOF
//tensorflow/lite
//tensorflow/compiler/mlir/lite
//tensorflow/compiler/mlir/tfrt
//tensorflow/core/runtime_fallback
//tensorflow/core/tfrt
//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks
EOF

  // Accumulate will forward op executions to the tape while the backward
  // function is running; this effectively adds the backward tape to the active
  // set (but does not require complicated callbacks to the language bindings).
  Status ForwardpropFromTape(
      const string& op_type, const std::vector<TapeTensor>& output_tensors,
      const std::function<BackwardFunction*()>& backward_function_getter,

  // threadpool, so that we avoid the possibility of running the runner_ in the
  // threadpool of GPU event mgr, as that can trigger more callbacks to be
  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).

    TFE_CancellationManager*);
TF_CAPI_EXPORT extern bool TFE_CancellationManagerRegisterCallback(
    TFE_CancellationManager*, TFE_CancellationToken token,
    const TFE_CancelCallback* c_callback, const char* callback_name);
TF_CAPI_EXPORT extern bool TFE_CancellationManagerDeregisterCallback(
    TFE_CancellationManager*, TFE_CancellationToken token);
TF_CAPI_EXPORT extern bool TFE_CancellationManagerTryDeregisterCallback(

low/compiler/mlir/tfrt/transforms/mlrt,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/runtime_fallback/test,tensorflow/core/runtime_fallback/test/gpu,tensorflow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test/testdata,tensorflow/core/tfrt/stubs,tensorflow/core/tfrt/...

// Set XLA's internal BuildXlaOpsPassFlags.tf_xla_enable_lazy_compilation to the
// value of 'enabled'. Also returns the original value of that flag.
//
// Use in tests to allow XLA to fallback to TF classic. This has global effect.
TF_CAPI_EXPORT unsigned char TF_SetXlaEnableLazyCompilation(
    unsigned char enable);
TF_CAPI_EXPORT unsigned char TF_SetTfXlaCpuGlobalJit(unsigned char enable);

  cat > $BATS_TEST_TMPDIR/ignore_deps_for_these_packages <<EOF
//tensorflow/lite
//tensorflow/compiler/mlir/lite
//tensorflow/compiler/mlir/tfrt
//tensorflow/core/runtime_fallback
//tensorflow/core/tfrt
//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks
EOF

*   Added `tf.keras.layers.SpectralNormalization` layer wrapper to perform spectral normalization on the weights of a target layer.