{1350244992, 300000000, "1350244992.3"},
		{1350244992, 23960100, "1350244992.0239601"},
		{1350244992, 23960108, "1350244992.023960108"},
		{+1, +1e9 - 1e0, "1.999999999"},
		{+1, +1e9 - 1e3, "1.999999"},
		{+1, +1e9 - 1e6, "1.999"},
		{+1, +0e0 - 0e0, "1"},
		{+1, +1e6 - 0e0, "1.001"},
		{+1, +1e3 - 0e0, "1.000001"},
		{+1, +1e0 - 0e0, "1.000000001"},
		{0, 1e9 - 1e0, "0.999999999"},
		{0, 1e9 - 1e3, "0.999999"},

	if w1 == w2 {
		panic("bad comparison")
	}
	x1 := [4]int16{-1, 88, 88, 88}
	x2 := [4]int16{-1, 99, 99, 99}
	if x1 == x2 {
		panic("bad comparison")
	}

	a1 := [2]int8{-1, 88}
	a2 := [2]int8{-1, 99}
	if a1 == a2 {
		panic("bad comparison")
	}
	b1 := [4]int8{-1, 88, 88, 88}
	b2 := [4]int8{-1, 99, 99, 99}
	if b1 == b2 {
		panic("bad comparison")
	}
	c1 := [8]int8{-1, 88, 88, 88, 88, 88, 88, 88}

    // CHECK: mhlo.compare  GT
    %values, %indices = "tf.ApproxTopK"(%0) {aggregate_to_topk = true, device = "", is_max_k = true, k = 10 : i64, recall_target = 0.949999988 : f32, reduction_dimension = -1 : i64, reduction_input_size_override = -1 : i64} : (tensor<10x500xbf16>) -> (tensor<10x10xbf16>, tensor<10x10xi32>)
    return %values : tensor<10x10xbf16>
  }

  // CHECK: %[[FACTOR:.*]] = mhlo.constant dense<1.00195694>
  // CHECK: %[[CORRECTED_VAR:.*]] = chlo.broadcast_multiply %[[VAR]], %[[FACTOR]]

  // CHECK-DAG: %[[ALPHA:.*]] = mhlo.constant dense<0.199999988>
  // CHECK-DAG: %[[BETA:.*]] = mhlo.constant dense<8.000000e-01>

  // CHECK: %[[ALPHA_MUL_OLD_MEAN:.*]] = chlo.broadcast_multiply %[[ALPHA]], %arg3