lru_list_.push_front(key);
  lra_list_.push_front(key);
  new_entry->lru_iterator = lru_list_.begin();
  new_entry->lra_iterator = lra_list_.begin();
  new_entry->timestamp = timer_seconds_();
  block_map_.emplace(std::make_pair(key, new_entry));
  return new_entry;
}

// Remove blocks from the cache until we do not exceed our maximum size.
void RamFileBlockCache::Trim() {
  while (!lru_list_.empty() && cache_size_ > max_bytes_) {

    // make the pointers invalid.
    all_input_tensors.reserve(num_inputs);
    for (int i = 0; i < num_inputs; ++i) {
      if (input_tensors[i] == nullptr) continue;
      all_input_tensors.emplace_back();
      Tensor& input_tensor = all_input_tensors.back();
      status->status = TF_TensorToTensor(input_tensors[i], &input_tensor);
      if (!status->status.ok()) return;
      input_tensors_vector[i] = &input_tensor;

      block_size, 2 * callers * block_size, 0, fetcher);
  std::vector<std::unique_ptr<Thread>> threads;
  threads.reserve(callers);
  for (int i = 0; i < callers; i++) {
    threads.emplace_back(
        Env::Default()->StartThread({}, "caller", [block_size, &cache, i]() {
          std::vector<char> out;
          TF_EXPECT_OK(
              ReadCache(&cache, "a", i * block_size, block_size, &out));

  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  const int num_devices = TF_DeviceListCount(devices);
  for (int i = 0; i < num_devices; ++i) {
    device_names.emplace_back(TF_DeviceListName(devices, i, status));
    EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  }
  TF_DeleteDeviceList(devices);
  TF_DeleteStatus(status);
  return device_names;

                       .c_str());
      return result;
    }
    children.erase(0, prefix.length());
    if (!children.empty() || include_self_directory_marker) {
      result.emplace_back(children);
    }
    ++count;
  }

  return result;
}

static bool FolderExists(GCSFile* gcs_file, std::string dir,
                         TF_Status* status) {

interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces

    env:
    {{- range $key, $value := .ProxyConfig.ProxyMetadata }}
    - name: {{ $key }}
      value: "{{ $value }}"
    {{- end }}
  {{- end }}
    resources:
  {{ template "resources" . }}
    securityContext:
      allowPrivilegeEscalation: {{ .Values.global.proxy.privileged }}
      privileged: {{ .Values.global.proxy.privileged }}
      capabilities:

    env:
    {{- range $key, $value := .ProxyConfig.ProxyMetadata }}
    - name: {{ $key }}
      value: "{{ $value }}"
    {{- end }}
  {{- end }}
    resources:
  {{ template "resources" . }}
    securityContext:
      allowPrivilegeEscalation: {{ .Values.global.proxy.privileged }}
      privileged: {{ .Values.global.proxy.privileged }}
      capabilities:

Jason van Zyl <******@****.***> 1243627215 +0000

       pulling in other changes.
 - [ ] Each commit in the pull request should have a meaningful subject line and body.
 - [ ] Format the pull request title like `[MNG-XXX] SUMMARY`,
       where you replace `MNG-XXX` and `SUMMARY` with the appropriate JIRA issue.
 - [ ] Also format the first line of the commit message like `[MNG-XXX] SUMMARY`.