}

Status ImmediateExecutionTensorHandle::SummarizeValue(
    std::string& summary) const {
  Status status;
  AbstractTensorPtr resolved(
      // TODO(allenl): Resolve should be const, and the caches that get updated
      // marked mutable.
      const_cast<ImmediateExecutionTensorHandle*>(this)->Resolve(&status));
  if (!status.ok()) {
    return status;
  }
  summary = resolved->SummarizeValue();

  // Note that `matches` is allocated by the plugin and freed by core
  // TensorFlow, so we need to use `plugin_memory_free_` here.
  char** matches = nullptr;
  const int num_matches = ops_->get_matching_paths(
      filesystem_.get(), pattern.c_str(), &matches, plugin_status.get());
  if (num_matches >= 0) {
    for (int i = 0; i < num_matches; i++) {
      result->push_back(std::string(matches[i]));

  virtual std::vector<string> ListFunctionNames() = 0;

  struct CacheStats {
    int64_t kernel_cache_size;
    int64_t device_cache_size;
    std::map<std::string, int64_t> func_kernel_cache_entries;
    int64_t local_rendezvous_cache_active_size;
  };
  virtual CacheStats GetCacheStats() = 0;

  //===--------------------------------------------------------------------===//

TF_CAPI_EXPORT extern TF_DeviceList* TFE_ContextListDevices(TFE_Context* ctx,
                                                            TF_Status* status);

// Clears the internal caches in the TFE context. Useful when reseeding random
// ops.
TF_CAPI_EXPORT extern void TFE_ContextClearCaches(TFE_Context* ctx);

// Sets a thread-local device placement policy. After this call, other calls to

# Sourcing this enables local disk cache
if [[ $(uname -s) == "Darwin" ]]; then
  echo "Please note that using disk cache on macOS is not recommended because the"
  echo "cache can end up being pretty big and make the build process inefficient."
fi

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

// is initialized (either locally or remotely). The context_id can change during
// the process lifetime although this should cause the worker to be
// reinitialized (e.g. cleared caches) as well.
TF_CAPI_EXPORT extern uint64_t TFE_GetContextId(TFE_Context* ctx);

// -----------------------------------------------------------------------------
// Cancellation APIs.

#   export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#   export TF_ANY_MODE=test
set -euxo pipefail
cd "$(dirname "$0")/../../"  # tensorflow/
export TFCI="$(echo $TFCI | sed 's/,nightly_upload/,public_cache,disk_cache/')"
git bisect start "$TF_BISECT_BAD" "$TF_BISECT_GOOD"

  TFE_ContextAddFunctionDef(ctx, function_def.data(), function_def.size(),
                            status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  for (bool clear_cache : {true, false, true}) {
    if (clear_cache) {
      TFE_ContextClearCaches(ctx);
    }
    TFE_TensorHandle* m = TestMatrixTensorHandle(ctx);
    TFE_TensorHandle* retval[1] = {nullptr};
    int num_retvals = 1;

      });

  uint64_t stat_cache_max_age = kStatCacheDefaultMaxAge;
  size_t stat_cache_max_entries = kStatCacheDefaultMaxEntries;
  const char* stat_cache_max_age_env = std::getenv(kStatCacheMaxAge);
  if (stat_cache_max_age_env &&
      absl::SimpleAtoi(stat_cache_max_age_env, &value)) {
    stat_cache_max_age = value;
  }
  const char* stat_cache_max_entries_env = std::getenv(kStatCacheMaxEntries);