// https://github.com/libimobiledevice/libimobiledevice.
package main

import (
	"bytes"
	"crypto/x509"
	"fmt"
	"os"
	"os/exec"
	"strings"
)

func main() {
	udids := getLines(exec.Command("idevice_id", "-l"))
	if len(udids) == 0 {
		fail("no udid found; is a device connected?")
	}

	mps := detectMobileProvisionFiles(udids)
	if len(mps) == 0 {

	export GOIOS_APP_ID=YYYYYYYY.some.bundle.id
	export GOIOS_TEAM_ID=ZZZZZZZZ

If you have multiple devices connected, specify the device UDID with the GOIOS_DEVICE_ID
variable. Use `idevice_id -l` to list all available UDIDs. Then, setting GOARCH to arm64
will select the device:

	GOOS=ios GOARCH=arm64 CGO_ENABLED=1 CC_FOR_TARGET=$(pwd)/../misc/ios/clangwrap.sh ./all.bash

class DeviceInfoCache;
class DeviceSet;

// Instances of DeviceId represent TensorFlow devices as integers.
//
// This helps avoid having to manipulate device names as strings when
// auto-clustering.
class DeviceId {
 public:
  DeviceId(DeviceId&&) = default;
  DeviceId(const DeviceId&) = default;
  DeviceId& operator=(const DeviceId&) = default;

  bool operator==(const DeviceId& other) const { return id() == other.id(); }

#include "absl/algorithm/container.h"
#include "absl/container/flat_hash_set.h"
#include "xla/status_macros.h"

namespace tensorflow {
namespace jit {

void DeviceSet::Insert(DeviceId device_id) {
  int word_index = device_id.id() / kWordSize;
  int bit_index = device_id.id() % kWordSize;
  const int storage_size = storage_.size();
  if (word_index >= storage_size) {
    storage_.resize(word_index + 1, 0);
  }

    TF_ASSERT_OK_AND_ASSIGN(jit::DeviceId device_id,
                            device_info_cache.GetIdFor(device_name));
    device_set.Insert(device_id);
    expected_devices.push_back(device_name);
  }

  device_set.ForEach([&](jit::DeviceId device_id) {
    actual_devices.push_back(string(device_info_cache.GetNameFor(device_id)));
    return true;
  });

    // instead.
    TF_ASSIGN_OR_RETURN(jit::DeviceId device_id,
                        device_info_cache->GetIdFor(n->assigned_device_name()));
    device_set.Insert(device_id);
  }

  TF_ASSIGN_OR_RETURN(jit::DeviceId result,
                      PickDeviceForXla(*device_info_cache, device_set,
                                       /*allow_mixing_unknown_and_cpu=*/true));

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  ASSERT_TRUE(absl::StrContains(device_type, "CPU")) << device_type;
  int device_id = TFE_TensorHandleDeviceID(hcpu, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  ASSERT_EQ(0, device_id) << device_id;

  // Disable the test if no GPU is present.
  string gpu_device_name;
  if (GetDeviceName(ctx, &gpu_device_name, "GPU")) {

  DeviceNameUtils::ParsedName parsed_name;
  tensorflow::DeviceNameUtils::ParseFullName(device_name, &parsed_name);
  std::string device_type = parsed_name.type;
  int device_id = 0;
  if (parsed_name.has_id) {
    device_id = parsed_name.id;
  }

  ctx.device_id = device_id;
  if (device_type == "CPU") {
    ctx.device_type = DLDeviceType::kDLCPU;
  } else if (device_type == "GPU") {
#if TENSORFLOW_USE_ROCM

	devs := []*pluginapi.Device{
		{ID: "ADeviceId", Health: pluginapi.Healthy},
	}

	p, e := esetup(t, devs, socket, "mock", func(n string, d []pluginapi.Device) {})
	defer ecleanup(t, p, e)
}

func TestRun(t *testing.T) {
	socket := filepath.Join(os.TempDir(), esocketName())

	devs := []*pluginapi.Device{
		{ID: "ADeviceId", Health: pluginapi.Healthy},

    return ",".join(map(str, sorted(query)))


@app.get("/query/list")
def get_query_list(device_ids: List[int] = Query()) -> List[int]:
    return device_ids


@app.get("/query/list-default")
def get_query_list_default(device_ids: List[int] = Query(default=[])) -> List[int]: