PLACEHOLDER_FOR_GREATER_OP_CODES = 127,
  CUMSUM = 128,
  CALL_ONCE = 129,
  BROADCAST_TO = 130,
  RFFT2D = 131,
  CONV_3D = 132,
  IMAG=133,
  REAL=134,
  COMPLEX_ABS=135,
  HASHTABLE = 136,
  HASHTABLE_FIND = 137,
  HASHTABLE_IMPORT = 138,
  HASHTABLE_SIZE = 139,
  REDUCE_ALL = 140,
  CONV_3D_TRANSPOSE = 141,
  VAR_HANDLE = 142,
  READ_VARIABLE = 143,
  ASSIGN_VARIABLE = 144,

  // CHECK: [[handle:%.*]] = "tf.HashTableV2"()
  // CHECK-SAME: container = ""
  // CHECK-SAME: key_dtype = !tf_type.string
  // CHECK-SAME: shared_name = "table"
  // CHECK-SAME: value_dtype = i32
  // CHECK-SAME: device = ""
  // CHECK-SAME: () -> tensor<!tf_type.resource>

 * limitations under the License.
 */

package org.gradle.internal.hash;

/**
 * A snapshot of the state of some thing.
 */
public interface Hashable {
    /**
     * Appends the snapshot to the given hasher.
     */
    void appendToHasher(Hasher hasher);

    Log-Output "Defender Preferences"
    Get-MpPreference
  }
}

# Converts the kube-env string in Yaml
#
# Returns: a PowerShell Hashtable object containing the key-value pairs from
#   kube-env.
function ConvertFrom_Yaml_KubeEnv {
  param (
    [parameter(Mandatory=$true)] [string]$kube_env_str
  )
  $kube_env_table = @{}
  $currentLine = $null

   * value, you should always choose it explicitly.
   *
   * <p>The current implementation uses the concurrency level to create a fixed number of hashtable
   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and

   * value, you should always choose it explicitly.
   *
   * <p>The current implementation uses the concurrency level to create a fixed number of hashtable
   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and

// Tests that the given vocabulary file does not exist.

func.func @init_all_tables() {
  %cst = arith.constant dense<"vocab_file_does_not_exist.txt"> : tensor<!tf_type.string>
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_/tmp/vocab.txt_-2_-1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

// Tests that the tf.InitializeTableFromTextFileV2 op are inlined.

func.func @init_all_tables() {
  %cst = arith.constant dense<"%FILE_PLACEHOLDER"> : tensor<!tf_type.string>
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_/tmp/vocab.txt_-2_-1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

func printTags(w io.Writer, rpt *Report) error {
	p := rpt.prof

	o := rpt.options
	formatTag := func(v int64, key string) string {
		return measurement.ScaledLabel(v, key, o.OutputUnit)
	}

	// Hashtable to keep accumulate tags as key,value,count.
	tagMap := make(map[string]map[string]int64)
	for _, s := range p.Sample {
		for key, vals := range s.Label {
			for _, val := range vals {
				valueMap, ok := tagMap[key]

// Tests that the tf.InitializeTableFromTextFileV2 op are inlined.

func.func @init_all_tables() {
  %cst = arith.constant dense<"tokens.txt"> : tensor<!tf_type.string>
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_/tmp/vocab.txt_-2_-1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>