panic(to)
				}
			}
		}()
	}
	wg.Wait()
}

func TestDynamicTimeoutHitMinimum(t *testing.T) {
	const minimum = 30 * time.Second
	timeout := newDynamicTimeout(time.Minute, minimum)

	initial := timeout.Timeout()

	const successTimeout = 20 * time.Second
	for range 100 {
		for range dynamicTimeoutLogSize {
			timeout.LogSuccess(successTimeout)
		}
	}

func TestScanLineNoNewline(t *testing.T) {
	const text = "abcdefghijklmn\nopqrstuvwxyz"
	lines := []string{
		"abcdefghijklmn",
		"opqrstuvwxyz",
	}
	testNoNewline(text, lines, t)
}

// Test that the line splitter handles a final line with a carriage return but no newline.
func TestScanLineReturnButNoNewline(t *testing.T) {
	const text = "abcdefghijklmn\nopqrstuvwxyz\r"
	lines := []string{

  TF_DeviceList* devices = TFE_ContextListDevices(ctx, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  const int num_devices = TF_DeviceListCount(devices);

  const char* kCPUDevice = "CPU:0";
  for (int i = 0; i < num_devices; ++i) {
    const string name(TF_DeviceListName(devices, i, status.get()));
    if (TF_GetCode(status.get()) != TF_OK) {

			default:
				a.Type = obj.TYPE_MEM
			}
			// fmt.Printf("CONST %d %s\n", a.Offset, obj.Dconv(&emptyProg, 0, a))
			p.expectOperandEnd()
			return
		}
		// fmt.Printf("offset %d \n", a.Offset)
	}

	// Register indirection: (reg) or (index*scale). We are on the opening paren.
	p.registerIndirect(a, prefix)
	// fmt.Printf("DONE %s\n", p.arch.Dconv(&emptyProg, 0, a))

func BenchmarkErasureEncodeQuick(b *testing.B) {
	const size = 12 * 1024 * 1024
	b.Run(" 00|00 ", func(b *testing.B) { benchmarkErasureEncode(2, 2, 0, 0, size, b) })
	b.Run(" 00|X0 ", func(b *testing.B) { benchmarkErasureEncode(2, 2, 0, 1, size, b) })
	b.Run(" X0|00 ", func(b *testing.B) { benchmarkErasureEncode(2, 2, 1, 0, size, b) })
}

func BenchmarkErasureEncode_4_64KB(b *testing.B) {
	const size = 64 * 1024

#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_status.h"

void RegisterLoggingDevice(TFE_Context* context, const char* name,
                           bool strict_scope_placement, bool* arrived_flag,
                           bool* executed_flag, TF_Status* status);
void AllocateLoggingDevice(const char* name, bool* arrived_flag,
                           bool* executed_flag, TFE_CustomDevice** device,

  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;
  DLManagedTensor tensor;

  explicit TfDlManagedTensorCtx(const TensorReference& ref) : reference(ref) {}
};

// Gets tensor from eager tensor handle.
const Tensor* GetTensorFromHandle(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");

  AbstractFunctionKind getKind() const { return kind_; }

  // Returns the AbstractFunction as a FunctionDef.
  virtual absl::Status GetFunctionDef(const FunctionDef**) = 0;

  // Returns a shared reference to the wrapped function.
  virtual absl::StatusOr<core::RefCountPtr<FunctionRecord>>
  GetFunctionRecord() = 0;

 private:
  const AbstractFunctionKind kind_;
};

using AbstractFunctionPtr =

	"github.com/minio/minio/internal/logger"
	"github.com/minio/pkg/v3/env"
)

const (
	logSubsys = "locking"
)

func lockLogIf(ctx context.Context, err error) {
	logger.LogIf(ctx, logSubsys, err)
}

// Enabled indicates object locking is enabled
const Enabled = "Enabled"

// RetMode - object retention mode.
type RetMode string

const (
	// RetGovernance - governance mode.
	RetGovernance RetMode = "GOVERNANCE"

	}))

	// local to remote
	remoteConn := local.Connection(remoteHost)
	remoteConn.WaitForConnect(t.Context())
	defer testlogger.T.SetErrorTB(t)()

	t.Run("localToRemote", func(t *testing.T) {
		const testPayload = "Hello Grid World!"

		start := time.Now()
		resp, err := remoteConn.Request(t.Context(), handlerTest, []byte(testPayload))
		errFatal(err)
		if string(resp) != testPayload {