{Name: "cpu", Weight: 1},
			},
		},
		{
			// Node1 scores on 0-MaxNodeScore scale
			// CPU Fraction: 300 / 250 = 100%
			// Memory Fraction: 600 / 1000 = 60%
			// Node1 Score: (100 + 60) / 2 = 80
			// Node2 scores on 0-MaxNodeScore scale
			// CPU Fraction: 100 / 250 = 40%
			// Memory Fraction: 200 / 1000 = 20%
			// Node2 Score: (20 + 40) / 2 = 30

	z2hi, _ := bits.Mul64(z2, ix)
	z1hi, z1lo := bits.Mul64(z1, ix)
	z0lo := z0 * ix
	lo, c := bits.Add64(z1lo, z2hi, 0)
	hi, _ := bits.Add64(z0lo, z1hi, c)
	// The top 3 bits are j.
	j = hi >> 61
	// Extract the fraction and find its magnitude.
	hi = hi<<3 | lo>>61
	lz := uint(bits.LeadingZeros64(hi))
	e := uint64(bias - (lz + 1))
	// Clear implicit mantissa bit and shift into place.
	hi = (hi << (lz + 1)) | (lo >> (64 - (lz + 1)))

			Namespace: namespace,
			Subsystem: subsystem,
			Name:      "priority_level_request_utilization",
			Help:      "Observations, at the end of every nanosecond, of number of requests (as a fraction of the relevant limit) waiting or in any stage of execution (but only initial stage for WATCHes)",
			// For executing: the denominator will be seats, so this metric will skew low.

type Cover struct {
	Mode            string
	Counters        map[string][]uint32
	Blocks          map[string][]CoverBlock
	CoveredPackages string
}

// Coverage reports the current code coverage as a fraction in the range [0, 1].
// If coverage is not enabled, Coverage returns 0.
//
// When running a large set of sequential test cases, checking Coverage after each one

// 'f' (-ddd.dddd, no exponent),
// 'g' ('e' for large exponents, 'f' otherwise),
// 'G' ('E' for large exponents, 'f' otherwise),
// 'x' (-0xd.ddddp±ddd, a hexadecimal fraction and binary exponent), or
// 'X' (-0Xd.ddddP±ddd, a hexadecimal fraction and binary exponent).
//
// The precision prec controls the number of digits (excluding the exponent)
// printed by the 'e', 'E', 'f', 'g', 'G', 'x', and 'X' formats.

	intVal     struct{ val *big.Int }   // Int values not representable as an int64
	ratVal     struct{ val *big.Rat }   // Float values representable as a fraction
	floatVal   struct{ val *big.Float } // Float values not representable as a fraction
	complexVal struct{ re, im Value }
)

func (unknownVal) Kind() Kind { return Unknown }
func (boolVal) Kind() Kind    { return Bool }

    that the device attribute exists.
  }];

  let constructor = "tensorflow::tf2xla::internal::CreateVerifyClusteringPass()";
}

def TPUClusterFormationPass : Pass<"tf-tpu-cluster-formation", "ModuleOp"> {
  let summary = "Forms clusters from operations assigned to the same TPU computation";

  let description = [{
    TPU computations from the frontend are composed of a `tf.TPUReplicateMetadata`

   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -
   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *
   * <p>The corresponding root-mean-square error in {@code x} as a function of {@code y} is a

//     sign_bit exponent_bits fraction_bits
//
//   Here, sign_bit is a single bit that designates the sign of the
//   number.
//
//   For float, there are 8 exponent bits and 23 fraction bits.
//
//   For double, there are 11 exponent bits and 52 fraction bits.
//
//   More details can be found at
//   http://en.wikipedia.org/wiki/IEEE_floating-point_standard.
//
// Template parameter:
//

 *     <li>Execution in isolated contexts such as an isolated classloader or even a separate process</li>
 *     <li>Safe execution of multiple tasks in parallel</li>
 * </ul>
 *
 * <p>Work should be submitted with a {@link WorkAction} class representing the implementation of the unit of work
 * and an action to configure the parameters of the unit of work (via {@link WorkParameters}).
 *
 * <pre>