Mac mac = Mac.getInstance("HmacMD5");
    mac.init(MD5_KEY);
    mac.update(input.getBytes(UTF_8));
    assertThat(HashCode.fromBytes(mac.doFinal()).toString()).isEqualTo(knownOutput);
    assertThat(HashCode.fromBytes(mac.doFinal(input.getBytes(UTF_8))).toString())
        .isEqualTo(knownOutput);
    assertThat(hmacMd5(MD5_KEY).hashString(input, UTF_8).toString()).isEqualTo(knownOutput);

        *   `tf.math.argmin`/`tf.math.argmax` for input data type `tf.bool` on
            CPU.
        *   `tf.nn.gelu` op for output data type `tf.float32` and quantization
            on CPU.
    *   Add nominal support for unsigned 16-bit integer tensor types. Note that
        very few TFLite kernels support this type natively, so its use in mobile
        ML authoring is generally discouraged.