assertEquals("9.999 \u03bcs", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(1234567);
    assertEquals("1.235 ms", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(5000000000L);
    assertEquals("5.000 s", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance((long) (1.5 * 60 * 1000000000L));

    A.reset(A_raw);
  }
  float B_vals[] = {.5f, -1.0f, 1.0f, 1.0f};
  int64_t B_dims[] = {2, 2};
  AbstractTensorHandlePtr B;
  {
    AbstractTensorHandle* B_raw;
    absl::Status s = TestTensorHandleWithDims<float, TF_FLOAT>(
        ctx_.get(), B_vals, B_dims, 2, &B_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    B.reset(B_raw);
  }

    assertEquals("9.999 \u03bcs", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(1234567);
    assertEquals("1.235 ms", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance(5000000000L);
    assertEquals("5.000 s", stopwatch.toString());
    stopwatch.reset();
    stopwatch.start();
    ticker.advance((long) (1.5 * 60 * 1000000000L));

    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, reader_->status());
      return;
    }
    var_to_shape_map_.reset(
        new TensorSliceReader::VarToShapeMap(reader_->GetVariableToShapeMap()));
    var_to_data_type_map_.reset(new TensorSliceReader::VarToDataTypeMap(

  istioctl admin log --revision v1

  # Reset levels of all the loggers to default value (info).
  istioctl admin log --reset
`,
		Aliases: []string{"l"},
		Args: func(logCmd *cobra.Command, args []string) error {
			if istiodReset && outputLogLevel != "" {
				logCmd.Println(logCmd.UsageString())
				return fmt.Errorf("--level cannot be combined with --reset")
			}
			if istiodReset && stackTraceLevel != "" {

	f, err := os.Open(path)
	if err != nil {
		return nil, err
	}

	bf := bytes.Buffer{}

	save := func(s string) {
		bf.WriteString(s + "\n")
	}
	reset := func() {
		bf.Reset()
	}

	ret := make(map[time.Duration][]string)

	s := bufio.NewScanner(f)
	s.Split(bufio.ScanLines)

	var (
		t            time.Duration
		skip, record bool
	)

	for s.Scan() {

func (b *Buffer) Truncate(n int) {
	if n == 0 {
		b.Reset()
		return
	}
	b.lastRead = opInvalid
	if n < 0 || n > b.Len() {
		panic("bytes.Buffer: truncation out of range")
	}
	b.buf = b.buf[:b.off+n]
}

// Reset resets the buffer to be empty,
// but it retains the underlying storage for use by future writes.
// Reset is the same as [Buffer.Truncate](0).
func (b *Buffer) Reset() {
	b.buf = b.buf[:0]
	b.off = 0

	if buf.Len() > m {
		t.Log("WARNING: TestEncodeDecodensScannerOptions Msgsize() is inaccurate")
	}

	vn := nsScannerOptions{}
	err := msgp.Decode(&buf, &vn)
	if err != nil {
		t.Error(err)
	}

	buf.Reset()
	msgp.Encode(&buf, &v)
	err = msgp.NewReader(&buf).Skip()
	if err != nil {
		t.Error(err)
	}
}

func BenchmarkEncodensScannerOptions(b *testing.B) {
	v := nsScannerOptions{}
	var buf bytes.Buffer

    Range(&vals, 0, num_dims_out);
    AbstractTensorHandle* sum_dims_raw = nullptr;
    TF_RETURN_IF_ERROR(TestTensorHandleWithDims<int32_t, TF_INT32>(
        ctx, vals.data(), vals_shape, 1, &sum_dims_raw));
    sum_dims.reset(sum_dims_raw);
  }

  // Reduce sum the output on all dimensions.
  TF_RETURN_IF_ERROR(ops::Sum(ctx, model_out.get(), sum_dims.get(), &outputs[0],
                              /*keep_dims=*/false, "sum_output"));

        }
    }

    /**
     * {@link ZipInputStream#reset()}の例外処理をラップするメソッドです。
     *
     * @param zis
     *            {@link ZipInputStream}。{@literal null}であってはいけません
     * @see ZipInputStream#reset()
     */
    public static void reset(final ZipInputStream zis) {
        assertArgumentNotNull("zis", zis);

        try {
            zis.reset();
        } catch (final IOException e) {