3\0B\03\1B\0F\1B\0B\0B\0B\0B\0B\0F\13\0B\0B\0B\0B\03\07\0F\17\07\02\A7\1F\05\0D\03\03\03\07\05\0F\03\0B\0B\1B\0D'\0F)\031\113\05\11\05\13\05\15\05\17\1D\15\17\05\19\17\19\EF\01\05\1B\03\03\1D\0D\05\1F!#%\1D\1D\1D\1F\1D!\1D##\03\03\03+\0D\03-/\1D%\1D'\1D)\1D+)\01\05\11\03\01\03\01\t\04A\05\01\11\01\05\07\03\01\05\03\11\01\t\05\03\05\0B\03\01\01\05\06\13\03\01\03\01\07\04\01\03\03\06\03\01\05\01\00\9A\04-\0F\0B\03!\1B\1D\05\1B\83/\1F\15\1D\15\11\13\15\11\11\0F\0B\11builtin\00vhlo\00module\00func_v...

//   - For GOARCH=arm, GOARM=5, 6, and 7
//     correspond to the arm.5, arm.6, and arm.7 feature build tags.
//   - For GOARCH=arm64, GOARM64=v8.{0-9} and v9.{0-5}
//     correspond to the arm64.v8.{0-9} and arm64.v9.{0-5} feature build tags.
//   - For GOARCH=mips or mipsle,
//     GOMIPS=hardfloat and softfloat
//     correspond to the mips.hardfloat and mips.softfloat

		{bucketName, objectName, uploadIDs[0], 4, "mnop", "e132e96a5ddad6da8b07bba6f6131fef", int64(len("abcd"))},
		// Part with size larger than 5 MiB.
		{bucketName, objectName, uploadIDs[0], 5, string(validPart), validPartMD5, int64(len(validPart))},
		{bucketName, objectName, uploadIDs[0], 6, string(validPart), validPartMD5, int64(len(validPart))},

		// Part with size larger than 5 MiB.

		if !exists {
			return
		}

		if bgSeq.lastHealActivity.IsZero() {
			return
		}

		metrics = make([]MetricV2, 0, 5)
		metrics = append(metrics, MetricV2{
			Description: getHealLastActivityTimeMD(),
			Value:       float64(time.Since(bgSeq.lastHealActivity)),
		})
		metrics = append(metrics, getObjectsScanned(bgSeq)...)

  // Setting the threshold to be 50% as a simple cost model heuristic. e.g. If 1
  // out of 2 concat inputs is an exception, we don't apply the hoist. If it's 1
  // out of 3, we do.
  const float exception_pct_threshold = 0.5;
  if (static_cast<float>(op.getValues().size()) * exception_pct_threshold <=
      exceptions.size())
    return failure();

  // Compute binary operands hoist parameters.

}

func.func @LRN(%arg0: tensor<2x3x4x5xf32>) -> tensor<2x3x4x5xf32> {
  %0 = "tf.LRN"(%arg0) {depth_radius = 5 :i64, bias = 1.0 :f32, alpha = 1.0 : f32, beta = 0.5 :f32} : (tensor<2x3x4x5xf32>) -> (tensor<2x3x4x5xf32>)
  func.return %0: tensor<2x3x4x5xf32>

  // CHECK-LABEL: LRN

	case ACMPU:
		return OPVCC(31, 32, 0, 0) | 1<<21
	case ACMPW:
		return OPVCC(31, 0, 0, 0) /* L=0 */
	case ACMPWU:
		return OPVCC(31, 32, 0, 0)
	case ACMPB:
		return OPVCC(31, 508, 0, 0) /* cmpb - v2.05 */
	case ACMPEQB:
		return OPVCC(31, 224, 0, 0) /* cmpeqb - v3.00 */

	case ACNTLZW:
		return OPVCC(31, 26, 0, 0)
	case ACNTLZWCC:
		return OPVCC(31, 26, 0, 1)
	case ACNTLZD:

個人.hk
个人.hk
箇人.hk
網络.hk
网络.hk
组織.hk
網絡.hk
网絡.hk
组织.hk
組織.hk
組织.hk

// hm : https://en.wikipedia.org/wiki/.hm
hm

// hn : http://www.nic.hn/politicas/ps02,,05.html
hn
com.hn
edu.hn
org.hn
net.hn
mil.hn
gob.hn

// hr : http://www.dns.hr/documents/pdf/HRTLD-regulations.pdf
hr
iz.hr
from.hr
name.hr
com.hr

The predeclared value <code>nil</code> cannot be used to initialize a variable
with no explicit type.
</p>

<pre>
var d = math.Sin(0.5)  // d is float64
var i = 42             // i is int
var t, ok = x.(T)      // t is T, ok is bool
var n = nil            // illegal
</pre>

<p>

"linewidth": 1, "links": [], "nullPointMode": "null", "percentage": false, "pointradius": 2, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "stack": false, "steppedLine": false, "targets": [ { "expr": "histogram_quantile(0.5, sum(rate(pilot_proxy_convergence_time_bucket[1m])) by (le))", "format": "time_series", "intervalFactor": 1, "legendFormat": "p50 ", "refId": "A" }, { "expr": "histogram_quantile(0.9, sum(rate(pilot_proxy_convergence_time_bucket[1m])) by (le))", "format":...