labels.facet_filetype_txt=filetype:txt\t\
labels.facet_filetype_others=filetype:others\n\

# ranking

# Window size for rank fusion.
rank.fusion.window_size=200
# Rank constant for rank fusion.
rank.fusion.rank_constant=20
# Number of threads for rank fusion.
rank.fusion.threads=-1
# Score field for rank fusion.
rank.fusion.score_field=rf_score

# acl

# Whether to get SMB roles from a file.
smb.role.from.file=true

                                              const char* attr_name,
                                              const char* value, size_t length);

// Set `num_dims` to -1 to represent "unknown rank".  Otherwise,
// `dims` points to an array of length `num_dims`.  `dims[i]` must be
// >= -1, with -1 meaning "unknown dimension".
TF_CAPI_EXPORT extern void TF_SetAttrShape(TF_OperationDescription* desc,

					<groupId>org.opensearch.plugin</groupId>
					<artifactId>aggs-matrix-stats-client</artifactId>
				</exclusion>
				<exclusion>
					<groupId>org.opensearch.plugin</groupId>
					<artifactId>rank-eval-client</artifactId>
				</exclusion>
				<exclusion>
					<groupId>org.opensearch.plugin</groupId>
					<artifactId>lang-expression</artifactId>
				</exclusion>
				<exclusion>

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(dims[0], returned_dims[0]);
  EXPECT_EQ(dims[1], returned_dims[1]);

  // Try to set 'unknown' with unknown rank on the shape and see that
  // it doesn't change.
  TF_GraphSetTensorShape(graph, feed_out_0, /*dims=*/nullptr, -1, s);
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

	if retryAttempts <= 0 {
		retryAttempts = batchReplJobDefaultRetries
	}
	delay := job.Replicate.Flags.Retry.Delay
	if delay <= 0 {
		delay = batchReplJobDefaultRetryDelay
	}
	rnd := rand.New(rand.NewSource(time.Now().UnixNano()))

	hasTags := len(r.Flags.Filter.Tags) != 0
	isMetadata := len(r.Flags.Filter.Metadata) != 0

func getRandomRange(minN, maxN int, seed int64) int {
	// special value -1 means no explicit seeding.
	if seed == -1 {
		return rand.New(rand.NewSource(time.Now().UnixNano())).Intn(maxN-minN) + minN
	}
	return rand.New(rand.NewSource(seed)).Intn(maxN-minN) + minN
}

// Randomizes the order of bytes in the byte array
// using Knuth Fisher-Yates shuffle algorithm.

				rs = append(rs, r)
			}
		}
	}
	// Shuffle the runes so that they are not in descending order.
	// The sort is deterministic since this is used for benchmarks,
	// which need to be repeatable.
	rr := rand.New(rand.NewSource(1))
	rr.Shuffle(len(rs), func(i, j int) {
		rs[i], rs[j] = rs[j], rs[i]
	})
	uchars := string(rs)

	return func(b *testing.B, n int) {
		buf := bmbuf[0:n]
		o := copy(buf, uchars)

	globalServerConfigMu.RLock()
	s := globalServerConfig
	globalServerConfigMu.RUnlock()

	sys.Lock()
	sys.iamRefreshInterval = iamRefreshInterval
	sys.Unlock()

	r := rand.New(rand.NewSource(time.Now().UnixNano()))

	var (
		openidInit bool
		ldapInit   bool
		authNInit  bool
		authZInit  bool
	)

	stsTLSConfig, err := xtls.Lookup(s[config.IdentityTLSSubSys][config.Default])

	// so various tasks will be useful
	bootstrapTrace("initAutoHeal", func() {
		initAutoHeal(GlobalContext, z)
	})

	// initialize the object layer.
	defer setObjectLayer(z)

	r := rand.New(rand.NewSource(time.Now().UnixNano()))
	attempt := 1
	for {
		var err error
		bootstrapTrace(fmt.Sprintf("poolMeta.Init: loading pool metadata, attempt: %d", attempt), func() {

	rand.Seed(time.Now().UnixNano())
	rand.Shuffle(len(allModels), func(i, j int) { allModels[i], allModels[j] = allModels[j], allModels[i] })
	DB.Migrator().DropTable("user_speaks", "user_friends", "ccc")

	if err := DB.Migrator().DropTable(allModels...); err != nil {
		t.Fatalf("Failed to drop table, got error %v", err)
	}