mergeAdjacentRanges(
        listOf(
          Mapping(0x0041, 0x0041, TYPE_MAPPED, "a".encodeUtf8()),
          Mapping(0x0042, 0x0042, TYPE_MAPPED, "b".encodeUtf8()),
        ),
      ),
    ).containsExactly(
      Mapping(0x0041, 0x0041, TYPE_MAPPED, "a".encodeUtf8()),
      Mapping(0x0042, 0x0042, TYPE_MAPPED, "b".encodeUtf8()),
    )
  }

  @Test fun simplifyCanonicalizesType() {
    assertThat(

  display: none;
  font-family: arial;
  font-size: 15px;
  line-height: 1em;
}

.daterangepicker:before, .daterangepicker:after {
  position: absolute;
  display: inline-block;
  border-bottom-color: rgba(0, 0, 0, 0.2);
  content: '';
}

.daterangepicker:before {
  top: -7px;
  border-right: 7px solid transparent;
  border-left: 7px solid transparent;
  border-bottom: 7px solid #ccc;
}

.daterangepicker:after {

    @JvmField val TLS_RSA_WITH_CAMELLIA_128_CBC_SHA = init("TLS_RSA_WITH_CAMELLIA_128_CBC_SHA", 0x0041)

    // @JvmField val TLS_DH_DSS_WITH_CAMELLIA_128_CBC_SHA = init("TLS_DH_DSS_WITH_CAMELLIA_128_CBC_SHA", 0x0042)
    // @JvmField val TLS_DH_RSA_WITH_CAMELLIA_128_CBC_SHA = init("TLS_DH_RSA_WITH_CAMELLIA_128_CBC_SHA", 0x0043)
    @JvmField val TLS_DHE_DSS_WITH_CAMELLIA_128_CBC_SHA = init("TLS_DHE_DSS_WITH_CAMELLIA_128_CBC_SHA", 0x0044)

normal;\n  word-spacing: normal;\n  white-space: normal;\n  line-break: auto;\n  font-size: 0.875rem;\n  word-wrap: break-word;\n  background-color: #fff;\n  background-clip: padding-box;\n  border: 1px solid rgba(0, 0, 0, 0.2);\n  border-radius: 0.3rem;\n  box-shadow: 0 0.25rem 0.5rem rgba(0, 0, 0, 0.2);\n}\n\n.popover .arrow {\n  position: absolute;\n  display: block;\n  width: 1rem;\n  height: 0.5rem;\n  margin: 0 0.3rem;\n}\n\n.popover .arrow::before, .popover .arrow::after {\n  position: absolute;\n...

c?v??dlq?sat?t&ca?n??wsn!.sloohcs????vog!.&a&s?w??civ?dlq?sat???wsn?zo??ti??c!.&bog?fni?gro?moc?t&an?en??ude??i??d&e!.tir.segap-tig,?iab??e!.&noitatsksid,odagod.citsalej,s&nd&ps,uolc,?ppatikria,?ysrab,??g!.&bew?gro?m&aug?oc??ofni?ten?ude?vog???h!.&0002?a&citore?idem?kitore??edszot?gro?ilus?letoh?m&alker?lif?t?urof??naltagni?o&c?ediv?fni?levynok?nisac??pohs?rarga?s&a&kal?zatu??emag?wen??t&lob?rops??virp?xe&s?zs??ytic?zsagoj??os?sut??l!.etisbew321,?m!.&ca?gro?moc?oc?ro?ten?vog???n!.&duolcesirpretn...

position: relative;\n  display: -ms-flexbox;\n  display: flex;\n  -ms-flex-direction: column;\n  flex-direction: column;\n  width: 100%;\n  pointer-events: auto;\n  background-color: #fff;\n  background-clip: padding-box;\n  border: 1px solid rgba(0, 0, 0, 0.2);\n  border-radius: 0.3rem;\n  outline: 0;\n}\n\n.modal-backdrop {\n  position: fixed;\n  top: 0;\n  left: 0;\n  z-index: 1040;\n  width: 100vw;\n  height: 100vh;\n  background-color: #000;\n}\n\n.modal-backdrop.fade {\n  opacity: 0;\n}\n\n.modal-backdrop.show...

    from that library.
*   tf.keras.optimizers default learning rate changes:
    *   Adadelta: 1.000 to 0.001
    *   Adagrad: 0.01 to 0.001
    *   Adamax: 0.002 to 0.001
    *   NAdam: 0.002 to 0.001

## Bug Fixes and Other Changes

*   Documentation
*   Deprecations and Symbol renames.
    *   Remove unused StringViewVariantWrapper