lra_list_.erase(block->lra_iterator);
        lra_list_.push_front(key);
        block->lra_iterator = lra_list_.begin();
        block->timestamp = timer_seconds_();
      }
    }
  });
  // Loop until either block content is successfully fetched, or our request
  // encounters an error.
  absl::MutexLock l(&block->mu);
  TF_SetStatus(status, TF_OK, "");
  while (true) {
    switch (block->state) {

      block_size, block_count * block_size, 0, fetcher);
  std::vector<char> out;
  out.resize(block_count, 0);
  // The cache has space for `block_count` blocks. The loop with i = 0 should
  // fill the cache, and the loop with i = 1 should be all cache hits. The
  // fetcher checks that it is called once and only once for each offset (to
  // fetch the corresponding block).
  for (int i = 0; i < 2; i++) {

                                                        TF_Status* status);

// Some TF ops need a step container to be set to limit the lifetime of some
// resources (mostly TensorArray and Stack, used in while loop gradients in
// graph mode). Calling this on a context tells it to start a step.
TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);

// Ends a step. When there is no active step (that is, every started step has

        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
    ],
)

tf_cc_test(
    name = "while_loop_test",
    size = "medium",
    srcs = ["while_loop_test.cc"],
    deps = [
        ":c_api",
        ":c_test_util",
        "//tensorflow/core:lib",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",

  TF_TriState auto_mixed_precision_onednn_bfloat16;
  TF_TriState auto_mixed_precision_mkl;
  TF_TriState pin_to_host_optimization;
  TF_TriState layout_optimizer;
  TF_TriState remapping;
  TF_TriState loop_optimization;
  TF_TriState dependency_optimization;
  TF_TriState auto_parallel;
  TF_TriState memory_optimization;
  TF_TriState scoped_allocator_optimization;
} TP_OptimizerConfigs;

  CONFIG_TOGGLE(auto_mixed_precision_onednn_bfloat16);
  CONFIG_TOGGLE(auto_mixed_precision_mkl);
  CONFIG_TOGGLE(pin_to_host_optimization);
  CONFIG_TOGGLE(layout_optimizer);
  CONFIG_TOGGLE(remapping);
  CONFIG_TOGGLE(loop_optimization);
  CONFIG_TOGGLE(dependency_optimization);
  CONFIG_TOGGLE(auto_parallel);
  CONFIG_TOGGLE(memory_optimization);
  CONFIG_TOGGLE(scoped_allocator_optimization);

// upstream gradients.
//
// TODO(apassos) provide concrete template instantiations for TFE_TensorHandle
// specialization, which is blocked by quite a few things needing to loop back
// into python now.
template <typename Gradient, typename BackwardFunction, typename TapeTensor>
class VSpace {
 public:
  virtual ~VSpace() {}

  // Returns the number of elements in the gradient tensor.