// registry name.
	// Note: the difference with `EDSUpdate` is that it only update the cache rather than requesting a push
	EDSCacheUpdate(shard ShardKey, hostname string, namespace string, entry []*IstioEndpoint)

	// SvcUpdate is called when a service definition is updated/deleted.
	SvcUpdate(shard ShardKey, hostname string, namespace string, event Event)

	// ConfigUpdate is called to notify the XDS server of config updates and request a push.

		services: []*Service{svc5_1, svc5_2},
	}

	env.EndpointIndex.shardsBySvc = map[string]map[string]*EndpointShards{
		svc5_1.Hostname.String(): {
			svc5_1.Attributes.Namespace: {
				Shards: map[ShardKey][]*IstioEndpoint{
					{Cluster: "Kubernets", Provider: provider.External}: {
						&IstioEndpoint{
							Address:         "1.1.1.1",
							EndpointPort:    7000,
							ServicePortName: "uds",
						},

      return mlir::failure();
    shard_output_types.push_back(shard_type);
    full_output_types.push_back(output.getType());
  }

  // Convert split sharded inputs to MANUAL sharded inputs.
  // common_split_sharding is the split sharding that is common to all inputs
  // and outputs.
  llvm::SmallVector<Value, 4> manual_inputs;
  manual_inputs.reserve(inputs.size());

  let hasVerifier = 1;
}

def TF_TPUPartitionedOutputOp : TF_Op<"TPUPartitionedOutput", [Pure]> {
  let summary = [{
An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned
  }];

  let description = [{
outputs outside the XLA computation.
  }];

  let arguments = (ins
    TF_Tensor:$inputs,

	registerStdTestSpecially := map[string]bool{
		// testdir can run normally as part of "go test std cmd", but because
		// it's a very large test, we register is specially as several shards to
		// enable better load balancing on sharded builders. Ideally the build
		// system would know how to shard any large test package.
		"cmd/internal/testdir": true,
	}

	// Fast path to avoid the ~1 second of `go list std cmd` when

```
### `-tf-tpu-sharding-identification`

_Identifies and handles inputs/outputs of TPU computation that is sharded across logical cores._

Bubbles up sharding configuration from `cluster_func` regions into
the attributes of `cluster_func`. This is done by parsing the