lor":"red","value":80}]},"unit":"ops"},"overrides":[]},"gridPos":{"h":3,"w":6,"x":0,"y":3},"id":20,"links":[],"maxDataPoints":100,"options":{"colorMode":"none","graphMode":"area","justifyMode":"auto","orientation":"horizontal","reduceOptions":{"calcs":["mean"],"fields":"","values":false},"textMode":"auto"},"pluginVersion":"10.1.5","targets":[{"datasource":{"type":"prometheus","uid":"${datasource}"},"expr":"round(sum(irate(istio_requests_total{reporter=\"source\"}[1m])), 0.001)","intervalFactor":...

  uint32_t num_replicas = replicate.getN();

  auto num_cores_per_replica_attr = cluster->getAttrOfType<mlir::IntegerAttr>(
      tensorflow::kNumCoresPerReplicaAttr);
  if (!num_cores_per_replica_attr)
    return cluster.emitOpError(
        CreateMissingAttributeMsg(tensorflow::kNumCoresPerReplicaAttr));
  int num_cores_per_replica = num_cores_per_replica_attr.getInt();

  auto topology_attr = cluster->getAttrOfType<StringAttr>("topology");

using ::tensorflow::tpu::ShardingAndIndex;

auto* phase2_bridge_compilation_status =
    tensorflow::monitoring::Counter<1>::New(
        "/tensorflow/core/tf2xla/api/v1/"
        "phase2_compilation_status", /*metric_name*/
        "Tracks the compilation status of the non-mlir bridge",
        /* metric description */ "status" /* metric label */);

auto* phase2_bridge_compilation_time = tsl::monitoring::Sampler<1>::New(

  mlir_to_hlo_args.rollout_state = rollout_state;
  mlir_to_hlo_args.mlir_module = mlir_module_str;

  se::Platform* platform =
      se::PlatformManager::PlatformWithName("Host").value();
  auto client =
      xla::ClientLibrary::GetOrCreateCompileOnlyClient(platform).value();

  std::vector<TensorShape> arg_shapes;
  TPUCompileMetadataProto metadata_proto;

directory: ${WORK_DIR}
ignoreVulnerability: true
dependencies:
${DEPENDENCIES:-$(cat <<EOD
  istio:
    localpath: ${ROOT}
  api:
    git: https://github.com/istio/api
    auto: modules
  proxy:
    git: https://github.com/istio/proxy
    auto: deps
  client-go:
    git: https://github.com/istio/client-go
    branch: master
  test-infra:
    git: https://github.com/istio/test-infra
    branch: master
  tools:

// OperationName.
void TfLiteBuiltinOpToMlir(const BuiltinOperatorSet& tflite_builtin_codes,
                           absl::flat_hash_set<std::string>& mlir_op_names) {
  for (const auto& entry : tflite_builtin_codes) {
    StringRef tflite_op_name = EnumNameBuiltinOperator(entry);
    std::string mlir_name = llvm::Twine("tfl.", tflite_op_name.lower()).str();
    mlir_op_names.insert(std::move(mlir_name));
  }

      volumes:
        {{ toYaml . | nindent 8 }}
      {{- end }}
      containers:
        - name: istio-proxy
          # "auto" will be populated at runtime by the mutating webhook. See https://istio.io/latest/docs/setup/additional-setup/sidecar-injection/#customizing-injection
          image: auto
          {{- with .Values.imagePullPolicy }}
          imagePullPolicy: {{ . }}
          {{- end }}
          securityContext:

				Result: simulation.Result{
					RouteMatched:   "default",
					ClusterMatched: "outbound|80||concrete.default.svc.cluster.local",
				},
			},
			// Auto
			{
				// No opaque host match for auto
				Name: "Auto virtual service applies to alias fqdn",
				Call: simulation.Call{Address: "1.2.3.4", Port: 81, Protocol: simulation.HTTP, HostHeader: "alias.default.svc.cluster.local", Path: "/one"},

    /**
     * If the module-path contains at least one filename-based auto-module, prepares a warning message.
     * The module path is the collection of dependencies associated to {@link JavaPathType#MODULES}.
     * It is caller's responsibility to send the message to a logger.
     *
     * @return warning message if at least one filename-based auto-module was found
     */
    Optional<String> warningForFilenameBasedAutomodules();

  options.toco_flags.set_allow_custom_ops(true);

  // Copy metadata for Reduced Precision Support from input model if it exists
  for (const auto& metadata : input_model.metadata) {
    if (metadata->name != tflite::optimize::kTfLiteReducedPrecisionKey) {
      continue;
    }

    const auto& data = input_model.buffers[metadata->buffer]->data;
    options.metadata[metadata->name] = std::string(data.begin(), data.end());
    break;
  }