*/
function computeStatistics(groupedFiles, fileMetadatas) {
    let totalAdditions = 0;
    let totalDeletions = 0
    let totalChangedFiles = 0;

    let summaries = [...groupedFiles.values()];
    Object.values(summaries).forEach(summary => {
        summary.additions = 0;
        summary.deletions = 0;

        summary.files.forEach(file => {
            let fileMetadata = metadataFor(fileMetadatas, file);

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

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:

        *   `setNumThreads` - Use `Interpreter.Options.setNumThreads`
    *   Add Conv3DTranspose as a builtin op.
*   `tf.summary`:
    *   Fix `tf.summary.should_record_summaries()` so it correctly reflects when
        summaries will be written, even when `tf.summary.record_if()` is not n
        effect, by returning True tensor if default writer is present.
*   Grappler: