EOF
}

function ips_to_cidrs() {
  IP_RANGE_START="$1"
  IP_RANGE_END="$2"
  python3 - <<EOF
from ipaddress import summarize_address_range, IPv4Address
[ print(n.compressed) for n in summarize_address_range(IPv4Address(u'$IP_RANGE_START'), IPv4Address(u'$IP_RANGE_END')) ]
EOF

    return methods_.summarize != nullptr;
  }

  Status SummarizeValue(std::string& summary) const override {
    if (methods_.summarize == nullptr) {
      return tensorflow::CustomDeviceTensorHandle::SummarizeValue(summary);
    }
    TF_Status c_status;
    std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> summary_buffer(
        methods_.summarize(data_, &c_status), TF_DeleteBuffer);

  int (*num_dims)(void* data, TF_Status* status);

  // Computes the axis length at `dim_index`.
  int64_t (*dim)(void* data, int dim_index, TF_Status* status);

  void (*deallocator)(void* data);

  // Summarizes the value of this tensor. The caller takes ownership of the
  // returned buffer. If `status` is not TF_OK, instead returns a null pointer.
  //
  // Does not include the shape and dtype of the tensor (which is generally

But all this functionality of using asynchronous code with `async` and `await` is many times summarized as using "coroutines". It is comparable to the main key feature of Go, the "Goroutines".

## Conclusion

Let's see the same phrase from above: