}
        outI++;
      }
      return outI == n ? hashTable : new Object[] {hashTable, outI, duplicateKey};
    } else {
      /*
       * Use 32 bits per entry.
       */
      int[] hashTable = new int[tableSize];
      Arrays.fill(hashTable, ABSENT);

      int outI = 0;
      entries:
      for (int i = 0; i < n; i++) {

// RUN: tf-opt %s -split-input-file -tfl-legalize-hashtables-tf --cse | FileCheck %s

// Test for case with string -> int64 hashtable.
func.func @hashtable_string_to_int64(%arg0: tensor<i64>) -> tensor<*xi64> {
  %cst = arith.constant dense<"f"> : tensor<!tf_type.string>

    // the textual format (on the commandline for example).
    return "quant-lift-hashtable-ops-as-args";
  }
  StringRef getDescription() const final {
    return "Lifts HashTable ops as function arguments.";
  }

  void runOnOperation() override;
};

// Checks if the given op is a Hashtable op.
bool IsHashTableOp(Operation* op) {
  return llvm::isa<TF::HashTableOp, TF::HashTableV2Op,

          int index = j & mask;
          if (hashTable[index] == null) {
            hashTable[index] = e;
            break;
          }
        }
      }
      return hashTable;
    }

    void ensureTableCapacity(int minCapacity) {
      int newTableSize;
      if (hashTable == null) {
        newTableSize = chooseTableSize(minCapacity);
        hashTable = new Object[newTableSize];

        }
    }

    @Test
    fun `can handle Hashtable`() {
        val hashtable = Hashtable<String, Any>(100)
        hashtable.put("key1", "value1")
        hashtable.put("key2", true)
        hashtable.put("key3", 42)
        configurationCacheRoundtripOf(hashtable).run {
            assertThat(hashtable, equalTo(this))
        }
    }

          ImmutableSet<E> result;
          if (hashTable != null && chooseTableSize(size) == hashTable.length) {
            @Nullable
            Object[] uniqueElements =
                shouldTrim(size, contents.length) ? Arrays.copyOf(contents, size) : contents;
            result =
                new RegularImmutableSet<E>(
                    uniqueElements, hashCode, hashTable, hashTable.length - 1, size);
          } else {

  // No needs to run the legalization patterns.
  if (hashtables.empty()) {
    return false;
  }

  for (auto hashtable : hashtables) {
    auto key_dtype = hashtable.getKeyDtype();
    auto value_dtype = hashtable.getValueDtype();

    // Only allow string -> int64 and int64 -> string mappings due to kernel
    // capability.
    if (!((mlir::isa<TF::StringType>(key_dtype) &&

/*
 * Cannot rely on Java serialization as
 * Hashtable's readObject() calls unsupported ObjectInputStream#readFields().
 */
val hashtableCodec: Codec<Hashtable<Any?, Any?>> = mapCodec { Hashtable(it) }


/*
 * Decodes Properties as Properties instead of Hashtable.
 */
val propertiesCodec: Codec<Properties> = mapCodec { Properties() }


val treeMapCodec: Codec<TreeMap<Any?, Any?>> = codec(
    {

   * part of the smeared hash of the element not covered by the hashtable mask, whereas the low bits
   * are the "next" pointer (pointing to the next entry in the bucket chain), which will always be
   * less than or equal to the hashtable mask.
   *
   * <pre>
   * hash  = aaaaaaaa
   * mask  = 00000fff
   * next  = 00000bbb
   * entry = aaaaabbb

   * part of the smeared hash of the element not covered by the hashtable mask, whereas the low bits
   * are the "next" pointer (pointing to the next entry in the bucket chain), which will always be
   * less than or equal to the hashtable mask.
   *
   * <pre>
   * hash  = aaaaaaaa
   * mask  = 00000fff
   * next  = 00000bbb
   * entry = aaaaabbb