// in an initialized context.
  for (auto d = devices.begin(); d != devices.end();) {
    if (absl::StrContains(d->get()->name(), "CPU:0")) {
      d = devices.erase(d);
    } else {
      ++d;
    }
  }

  status->status = tensorflow::unwrap(ctx)->AddDevices(std::move(devices));
}

void TFE_InsertConfigKeyValue(TFE_Context* ctx, const char* key,

}

// ContainerInfo contains information required by the runtime to consume prepared resources.
type ContainerInfo struct {
	// The Annotations for the container
	Annotations []kubecontainer.Annotation
	// CDI Devices for the container
	CDIDevices []kubecontainer.CDIDevice

// verification is empty or invalid.
var errBitrotHashAlgoInvalid = StorageErr("bit-rot hash algorithm is invalid")

// errCrossDeviceLink - rename across devices not allowed.
var errCrossDeviceLink = StorageErr("Rename across devices not allowed, please fix your backend configuration")

// errLessData - returned when less data available than what was requested.

	// UpdateQOSCgroups performs housekeeping updates to ensure that the top
	// level QoS containers have their desired state in a thread-safe way
	UpdateQOSCgroups() error

	// GetResources returns RunContainerOptions with devices, mounts, and env fields populated for
	// extended resources required by container.
	GetResources(pod *v1.Pod, container *v1.Container) (*kubecontainer.RunContainerOptions, error)

// RUN: tf-opt %s -tf-replicated-clustering-bridge-v1 | FileCheck %s

module attributes {tf.devices = ["/job:localhost/replica:0/task:0/device:CPU:0", "/job:localhost/replica:0/task:0/device:TPU:0", "/job:localhost/replica:0/task:0/device:TPU:1", "/job:localhost/replica:0/task:0/device:TPU_SYSTEM:0"], tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 296 : i32}} {
  func.func @main() {
// CHECK: arith.constant
// CHECK: TPUCompile
// CHECK: TPUExecute

#include "tensorflow/core/lib/core/status.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {

// Run all the passes involved in transforming the graph before execution so
// that it is suitable for targeting devices when called with the TF 2 Function
// API. Users that need clustering with the Session API should use the v1 Bridge
// API. These transformations take as input a Tensorflow Graph as an MLIR Module

// so there is no risk of polluting the entire cache with data accessed once.
// Another goal of DirectIO is to minimize the mutation of data by the kernel
// before issuing IO to underlying devices. ZFS users often enable features like
// compression and checksumming which currently necessitates mutating data in
// the kernel.
//
// DirectIO semantics for a filesystem like ZFS would be quite different than

		case "ios":
			if isCorelliumBuilder(b) {
				// The corellium environment is self-hosting, so it should be able
				// to build even though real "ios" devices can't exec.
			} else {
				// The usual iOS sandbox does not allow the app to start another
				// process. If we add builders on stock iOS devices, they presumably
				// will not be able to exec, so we may as well allow that now.
				t.Logf("HasGoBuild is false on %s", b)
				return
			}

    options.flib_def = &library;
    options.graph = graph;
    return options;
  }

  FunctionLibraryDefinition library;
  SessionOptions session_options;
};

// Helps set up devices for unit tests.
class DeviceSetup {
 public:
  void AddDevicesAndSetUp(
      const std::vector<std::string>& device_names,
      const std::optional<FunctionDef>& fdef = std::nullopt);

		// enough (4.11+), we can read the arm64 registers directly which'll
		// trap into the kernel and then return back to userspace.
		//
		// But on older kernels, such as Linux 4.4.180 as used on many Synology
		// devices, calling readARM64Registers (specifically getisar0) will
		// cause a SIGILL and we'll die. So for older kernels, parse /proc/cpuinfo
		// instead.
		//
		// See golang/go#57336.
		if linuxKernelCanEmulateCPUID() {