echo "about to  ${results_jq}..."
    cat -n "${results_jq}"
    echo
  fi
  <"${spec_summaries}" jq --slurp --from-file "${results_jq}" > "${results_json}"
}

# summarize e2e test policy results
# output to ${summary_json}
function generate_summary_json() {
  summary_jq=${tmpdir}/summary.jq
  cat >"${summary_jq}" <<EOS
  . as \$results |
  # for each policy category

Gradle lets us know the outcome of each task in the console output:

- `FROM-CACHE` - tasks have been fetched from the local build cache.
- `UP-TO-DATE` - tasks that used incremental build and were not re-run.

To summarize:

1. First, we used the `build` task to populate our local cache with task inputs and outputs -- we can imagine this was done a week ago.

    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);

  %3 = "tf.StringFormat"(%2) {__op_key = 1: i32, device = "/job:localhost/replica:0/task:0/device:CPU:0", placeholder = "{}", strtemplate = "%s", summarize = 3 : i64, template = "Outside compiled {}"} : (tensor<i32>) -> tensor<!tf_type.string>

		y := p.chunkOf(sc).summarize()
		if x == y {
			return
		}
		p.summary[len(p.summary)-1][sc] = y
	} else if contig {
		// Slow contiguous path: the allocation spans more than one chunk
		// and at least one summary is guaranteed to change.
		summary := p.summary[len(p.summary)-1]

		// Update the summary for chunk sc.
		summary[sc] = p.chunkOf(sc).summarize()

                val currentFingerprint = host.fingerprintOf(fileSystemInputs)
                if (currentFingerprint != fileSystemInputsFingerprint) {
                    // TODO: summarize what has changed (see https://github.com/gradle/configuration-cache/issues/282)
                    return "an input to $workDisplayName has changed"
                }
            }

  TFE_CustomDeviceTensorHandleMethods handle_methods;
  handle_methods.num_dims = &ParallelTensorNumDims;
  handle_methods.dim = &ParallelTensorDim;
  handle_methods.deallocator = &ParallelTensorDeallocator;
  handle_methods.summarize = &ParallelTensorSummarize;
  return TensorHandlePtr(TFE_NewCustomDeviceTensorHandle(
      context, parallel_device_name.c_str(), t_released->dtype(), t_released,
      handle_methods, status));
}

)

// UserRegionsHandlerFunc returns a HandlerFunc that reports all regions found in the trace.
func UserRegionsHandlerFunc(t *parsedTrace) http.HandlerFunc {
	return func(w http.ResponseWriter, r *http.Request) {
		// Summarize all the regions.
		summary := make(map[regionFingerprint]regionStats)
		for _, g := range t.summary.Goroutines {
			for _, r := range g.Regions {
				id := fingerprintRegion(r)
				stats, ok := summary[id]
				if !ok {

- `context_values`: are values like the bucket and object name and other information which should be cryptographically bound to the KEK.

To summarize for any encrypted object there exists (at least) three different keys:

func (b *PallocBits) Free(i, n uint)             { (*pallocBits)(b).free(i, n) }
func (b *PallocBits) Summarize() PallocSum       { return PallocSum((*pallocBits)(b).summarize()) }
func (b *PallocBits) PopcntRange(i, n uint) uint { return (*pageBits)(b).popcntRange(i, n) }

// SummarizeSlow is a slow but more obviously correct implementation
// of (*pallocBits).summarize. Used for testing.
func SummarizeSlow(b *PallocBits) PallocSum {
	var start, most, end uint