ASSERT_EQ(op_list.op_size(), 1);
    EXPECT_EQ("TestCApi1", op_list.op(0).name());
    TF_DeleteLibraryHandle(lib);
  }
#endif  // !defined(TENSORFLOW_NO_SHARED_OBJECTS)
  {
    TF_Buffer* op_list_buffer = TF_GetAllOpList();
    tensorflow::OpList op_list;
    op_list.ParseFromArray(op_list_buffer->data, op_list_buffer->length);
    ASSERT_GE(op_list.op_size(), 1);

      }
      // Float
      if (const int f_size = default_value.list().f_size()) {
        absl::InlinedVector<float, 4> f_vector;
        f_vector.reserve(f_size);
        for (int i = 0; i < f_size; ++i) {
          f_vector.push_back(default_value.list().f(i));
        }
        TFE_OpSetAttrFloatList(op, attr_name, f_vector.data(), f_size);
      }
      // Bool

// Payload size can give an indication of expected payload size.
// If plSize is <= 0 it will be calculated.
func (x *xlMetaInlineData) serialize(plSize int, keys [][]byte, vals [][]byte) {
	if len(keys) != len(vals) {
		panic(fmt.Errorf("xlMetaInlineData.serialize: keys/value number mismatch"))
	}
	if len(keys) == 0 {
		*x = nil
		return
	}
	if plSize <= 0 {
		plSize = 1 + msgp.MapHeaderSize
		for i := range keys {

    public MimeMap() throws IOException {
        int n;

        in = new byte[IN_SIZE];
        InputStream is = getClass().getClassLoader().getResourceAsStream( "jcifs/smb1/util/mime.map" );

        inLen = 0;
        while(( n = is.read( in, inLen, IN_SIZE - inLen )) != -1 ) {
            inLen += n;
        }
        if( inLen < 100 || inLen == IN_SIZE ) {

		},
	}

	tests := []struct {
		filter  Filter
		objSize int64
		want    bool
	}{
		{
			filter:  fiLt,
			objSize: 101 * humanize.MiByte,
			want:    false,
		},
		{
			filter:  fiLt,
			objSize: 99 * humanize.MiByte,
			want:    true,
		},
		{
			filter:  fiGt,
			objSize: 1*humanize.MiByte - 1,
			want:    false,
		},
		{
			filter:  fiGt,

	tests := []struct {
		objSize    int64
		sizeFilter BatchJobSizeFilter
		want       bool
	}{
		{
			// 1Mib < 2Mib < 10MiB -> in range
			objSize: 2 << 20,
			sizeFilter: BatchJobSizeFilter{
				UpperBound: 10 << 20,
				LowerBound: 1 << 20,
			},
			want: true,
		},
		{
			// 2KiB < 1 MiB -> out of range from left
			objSize: 2 << 10,
			sizeFilter: BatchJobSizeFilter{

func runPutObjectBenchmark(b *testing.B, obj ObjectLayer, objSize int) {
	var err error
	// obtains random bucket name.
	bucket := getRandomBucketName()
	// create bucket.
	err = obj.MakeBucket(context.Background(), bucket, MakeBucketOptions{})
	if err != nil {
		b.Fatal(err)
	}

	// get text data generated for number of bytes equal to object size.
	textData := generateBytesData(objSize)
	// generate md5sum for the generated data.

    assertEquals(map.size(), oldSize - 1);
    assertFalse(map.containsKey(key));
    assertEquals(subMap.size(), oldSize - 2);
  }

  public void testTailMapClearThrough() {
    SortedMap<K, V> map;
    try {
      map = makePopulatedMap();
    } catch (UnsupportedOperationException e) {
      return;
    }
    int oldSize = map.size();
    if (map.size() < 2 || !supportsClear) {

        public String remark;
        public int permissions;
        public int max_uses;
        public int current_uses;
        public String path;
        public String password;
        public int sd_size;
        public byte[] security_descriptor;

        public void encode(NdrBuffer _dst) throws NdrException {
            _dst.align(4);
            _dst.enc_ndr_referent(netname, 1);

  }

  @CollectionSize.Require(absent = ZERO)
  @MapFeature.Require({SUPPORTS_REMOVE, SUPPORTS_PUT})
  public void testPropagatesRemoveThenAddToMultimap() {
    int oldSize = getNumElements();

    Collection<V> result = multimap().asMap().get(k0());
    assertTrue(result.remove(v0()));

    assertFalse(multimap().containsKey(k0()));