maxs[i] = std::max(maxs[i], 0.0);
      mins[i] = std::min(mins[i], 0.0);
    }
    if (symmetric) {
      for (int i = 0; i < dim_size; ++i) {
        maxs[i] = std::max(std::abs(mins[i]), std::abs(maxs[i]));
        mins[i] = -maxs[i];
      }
    }
  }
}

Type GetUniformQuantizedTypeForWeight(
    const ElementsAttr attr, const bool symmetric, const unsigned num_bits,

	abs := fmt.Sprintf("%#x", curr)
	if prevInfo == nil {
		return abs
	}

	prev := prevInfo.Address
	if prev == curr {
		return "*"
	}

	diff := int64(curr - prev)
	relative := fmt.Sprintf("%+d", diff)

	// Only bother to use the relative address if it is actually shorter.
	if len(relative) < len(abs) {
		return relative
	}

// This is known as "black box" testing.
//
//	package abs_test
//
//	import (
//		"testing"
//
//		"path_to_pkg/abs"
//	)
//
//	func TestAbs(t *testing.T) {
//	    got := abs.Abs(-1)
//	    if got != 1 {
//	        t.Errorf("Abs(-1) = %d; want 1", got)
//	    }
//	}
//
// For more detail, run "go help test" and "go help testflag".
//
// # Benchmarks
//

		}
		// and turn it into a float64
		x := math.Float64frombits(binary.LittleEndian.Uint64(b))
		if math.IsNaN(x) || math.IsInf(x, 0) {
			continue
		}
		x = math.Abs(x)
		if x < 0x1p-1000 { // avoid underflow patterns
			continue
		}
		frac, _ := math.Frexp(x) // 52 bits of randomness
		return frac*2 - 1
	}

}

// CHECK-LABEL:   func @abs(
// CHECK-SAME:              %[[VAL_0:.*]]: tensor<2xf32>) -> tensor<2xf32> {
// CHECK:           %[[VAL_1:.*]] = "tf.Abs"(%[[VAL_0]]) : (tensor<2xf32>) -> tensor<2xf32>
// CHECK:           return %[[VAL_1]] : tensor<2xf32>
// CHECK:         }
func.func @abs(%arg0: tensor<2xf32>) -> tensor<2xf32> {
  %0 = "mhlo.abs"(%arg0) : (tensor<2xf32>) -> tensor<2xf32>

    // CHECK-DAG: %[[SIGN:.*]] = "tf.Sign"(%[[PROX]]) : (tensor<4xf32>) -> tensor<4xf32>
    // CHECK-DAG: %[[ABS:.*]] = "tf.Abs"(%[[PROX]]) : (tensor<4xf32>) -> tensor<4xf32>
    // CHECK-DAG: %[[SCALED_L1:.*]] = "tf.Mul"(%[[ADAGRAD_LR]], %[[L1]]) : (tensor<4xf32>, tensor<f32>) -> tensor<4xf32>
    // CHECK-DAG: %[[PROX_NEW:.*]] = "tf.Sub"(%[[ABS]], %[[SCALED_L1]]) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>

	}

	// Pass in relative days from current time, to additionally
	// to verify "object-lock-remaining-retention-days" policy if any.
	days := int(math.Ceil(math.Abs(objRetention.RetainUntilDate.Sub(t).Hours()) / 24))

	ret := objectlock.GetObjectRetentionMeta(oi.UserDefined)
	if ret.Mode.Valid() {
		// Retention has expired you may change whatever you like.

// A particular pattern seen in cgo code:
(AND (MOVDconst [c]) x:(MOVBZload _ _)) => (ANDconst [c&0xFF] x)

// floating point negative abs
(FNEG (F(ABS|NABS) x)) => (F(NABS|ABS) x)

// floating-point fused multiply-add/sub
(F(ADD|SUB) (FMUL x y) z) && x.Block.Func.useFMA(v) => (FM(ADD|SUB) x y z)
(F(ADDS|SUBS) (FMULS x y) z) && x.Block.Func.useFMA(v) => (FM(ADDS|SUBS) x y z)

	hash.Write([]byte(fDistinguisher))
	var sum [32]byte
	hash.Sum(sum[:0])
	return binary.LittleEndian.Uint64(sum[:8])
}

func relDiff(x, y float64) float64 {
	diff := math.Abs(x - y)
	den := math.Max(math.Abs(x), math.Abs(y))
	if den == 0 {
		return 0
	}
	return diff / den
}

  // Refer to the implementation in
  // tensorflow/lite/kernels/range.cc.
  return std::is_integral<FloatOrInt>::value
             ? ((std::abs(limit - start) + std::abs(delta) - 1) /
                std::abs(delta))
             : std::ceil(std::abs((limit - start) / delta));
}

// Builds a constant range tensor of `result_elem_type` elements.
// Template parameter `FloatOrIntAtrr` must be mlir::IntegerAttr or