%default = "tf.Const"() {value = dense<-1> : tensor<i64>} : () -> tensor<i64>
  %handle = "tf.HashTableV2"() {container = "", device = "/job:localhost/replica:0/task:0/device:CPU:0", key_dtype = !tf_type.string, shared_name = "hash_table", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>


  %keys = "tf.Const"() {value = dense<["a", "b", "c", "d"]> : tensor<4x!tf_type.string>} : () -> tensor<4x!tf_type.string>

 * elements, including {@code null}, are permitted.
 *
 * <p>{@code contains(x)}, {@code add(x)} and {@code remove(x)}, are all (expected and amortized)
 * constant time operations. Expected in the hashtable sense (depends on the hash function doing a
 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *

 * elements, including {@code null}, are permitted.
 *
 * <p>{@code contains(x)}, {@code add(x)} and {@code remove(x)}, are all (expected and amortized)
 * constant time operations. Expected in the hashtable sense (depends on the hash function doing a
 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *

// pass is a part of the ConvertTpuModelToCpu pass to support BF16 optimized TPU
// model quantization.
std::unique_ptr<OperationPass<ModuleOp>> CreateCastBf16OpsToF32Pass();

// Creates a pass that lifts HashTable ops as function arguments. In the graph
// execution mode, resource ops with the same `shared_name` attribute point to
// the same underlying resource. This is not true in the eager execution mode.

 * remove) are supported. Null keys and values are supported.
 *
 * <p>{@code containsKey(k)}, {@code put(k, v)} and {@code remove(k)} are all (expected and
 * amortized) constant time operations. Expected in the hashtable sense (depends on the hash
 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *

          (LinkedHashMultimap.ValueSet) multimap.backingMap().get("a");
      assertEquals(z, valueSet.size());
      assertFalse(
          Hashing.needsResizing(
              valueSet.size(),
              valueSet.hashTable.length,
              LinkedHashMultimap.VALUE_SET_LOAD_FACTOR));
    }
  }

  private Multimap<String, Integer> initializeMultimap5() {
    Multimap<String, Integer> multimap = LinkedHashMultimap.create();

  (TF_VariableV2Op:$dest $shape, $container, $shard_name),
  [], [(CopyAttrs $src, $dest)]>;


//===----------------------------------------------------------------------===//
// Canonicalize tf.HashTable and its user ops to V2 versions.
//===----------------------------------------------------------------------===//
def HashTableAndInitializeTableToV2 : Pat<
  (TF_InitializeTableFromTextFileOp:$src (TF_HashTableOp $container,

    return findEntry(value, valueHash, hashTableVToK, nextInBucketVToK, values);
  }

  int findEntry(
      @CheckForNull Object o,
      int oHash,
      int[] hashTable,
      int[] nextInBucket,
      @Nullable Object[] array) {
    for (int entry = hashTable[bucket(oHash)]; entry != ABSENT; entry = nextInBucket[entry]) {
      if (Objects.equal(array[entry], o)) {
        return entry;
      }
    }
    return ABSENT;

	// behave differently.
	m[nan] = 1
	m[nan] = 2
	m[nan] += 4

	cnt := 0
	s := 0
	growflag := true
	for k, v := range m {
		if growflag {
			// force a hashtable resize
			for i := 0; i < 50; i++ {
				m[float64(i)] = i
			}
			for i := 50; i < 100; i++ {
				m[float64(i)] += i
			}
			growflag = false
		}
		if k != k {
			cnt++
			s |= v
		}

  let constructor = "CreateInsertCallOnceOpFromSessionInitializerPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}

def LegalizeHashTablesPass : Pass<"tfl-legalize-hashtables-tf", "mlir::ModuleOp"> {
  let summary = "Legalize TensorFlow hash tables to TensorFlow Lite dialect.";
  let constructor = "CreateLegalizeHashTablesPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}