pkg debug/elf, const R_LARCH_COPY R_LARCH #46229
pkg debug/elf, const R_LARCH_IRELATIVE = 12 #46229
pkg debug/elf, const R_LARCH_IRELATIVE R_LARCH #46229
pkg debug/elf, const R_LARCH_JUMP_SLOT = 5 #46229
pkg debug/elf, const R_LARCH_JUMP_SLOT R_LARCH #46229
pkg debug/elf, const R_LARCH_MARK_LA = 20 #46229
pkg debug/elf, const R_LARCH_MARK_LA R_LARCH #46229
pkg debug/elf, const R_LARCH_MARK_PCREL = 21 #46229

pkg debug/elf, const R_RISCV_HI20 = 26
pkg debug/elf, const R_RISCV_HI20 R_RISCV
pkg debug/elf, const R_RISCV_JAL = 17
pkg debug/elf, const R_RISCV_JAL R_RISCV
pkg debug/elf, const R_RISCV_JUMP_SLOT = 5
pkg debug/elf, const R_RISCV_JUMP_SLOT R_RISCV
pkg debug/elf, const R_RISCV_LO12_I = 27
pkg debug/elf, const R_RISCV_LO12_I R_RISCV
pkg debug/elf, const R_RISCV_LO12_S = 28
pkg debug/elf, const R_RISCV_LO12_S R_RISCV

        // We only ever register ArrayReferences with the queue so this is always safe.
        ArrayReference<? extends L> arrayRef = (ArrayReference<? extends L>) ref;
        // Try to clear out the array slot, n.b. if we fail that is fine, in either case the
        // arrayRef will be out of the array after this step.
        locks.compareAndSet(arrayRef.index, arrayRef, null);
      }
    }

    @Override

      int hash = element.hashCode();
      for (int j = Hashing.smear(hash); ; j++) {
        int index = j & mask;
        Object value = table[index];
        if (value == null) {
          // Came to an empty slot. Put the element here.
          elements[uniques++] = element;
          table[index] = element;
          hashCode += hash;
          break;
        } else if (value.equals(element)) {
          break;

pkg debug/elf, const R_PPC64_GOT_TPREL16_HI R_PPC64
pkg debug/elf, const R_PPC64_GOT_TPREL16_LO_DS = 88
pkg debug/elf, const R_PPC64_GOT_TPREL16_LO_DS R_PPC64
pkg debug/elf, const R_PPC64_JMP_SLOT = 21
pkg debug/elf, const R_PPC64_JMP_SLOT R_PPC64
pkg debug/elf, const R_PPC64_NONE = 0
pkg debug/elf, const R_PPC64_NONE R_PPC64
pkg debug/elf, const R_PPC64_REL14 = 11
pkg debug/elf, const R_PPC64_REL14 R_PPC64

    //     fgha[c]|[b]de -> fgha[b]|[c]de. Because these two blocks are the same size, we are done.
    // The Dolphin algorithm is attractive because it does the fewest array reads and writes: each
    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two

  static final class Whitespace extends NamedFastMatcher {

    // TABLE is a precomputed hashset of whitespace characters. MULTIPLIER serves as a hash function
    // whose key property is that it maps 25 characters into the 32-slot table without collision.
    // Basically this is an opportunistic fast implementation as opposed to "good code". For most
    // other use-cases, the reduction in readability isn't worth it.
    static final String TABLE =

  static final class Whitespace extends NamedFastMatcher {

    // TABLE is a precomputed hashset of whitespace characters. MULTIPLIER serves as a hash function
    // whose key property is that it maps 25 characters into the 32-slot table without collision.
    // Basically this is an opportunistic fast implementation as opposed to "good code". For most
    // other use-cases, the reduction in readability isn't worth it.
    static final String TABLE =

      advanced use cases can also write their own custom
      `tf.train.experimental.ShardingCallback`s.

* `tf.train.CheckpointOptions`
    * Added `experimental_skip_slot_variables` (a boolean option) to skip
    restoring of optimizer slot variables in a checkpoint.

*   `tf.saved_model.SaveOptions`

    * `SaveOptions` now takes a new argument called

      "options": {
        "alertThreshold": true
      },
      "percentage": false,
      "pluginVersion": "10.0.2",
      "pointradius": 2,
      "points": false,
      "renderer": "flot",
      "seriesOverrides": [],
      "spaceLength": 10,
      "stack": false,
      "steppedLine": false,
      "targets": [
        {
          "datasource": {
            "type": "prometheus",