union QuantizationDetails {
  CustomQuantization,
}

// Parameters for converting a quantized tensor back to float.
table QuantizationParameters {
  // These four parameters are the asymmetric linear quantization parameters.
  // Given a quantized value q, the corresponding float value f should be:
  //   f = scale * (q - zero_point)
  // For other quantization types, the QuantizationDetails below is used.

//
//   - 1e43 ≈ (0xE596B7B0_C643C719                   * (2 ** 79))
//   - 1e43 = (0xE596B7B0_C643C719_6D9CCD05_D0000000 * (2 ** 15))
//
// The mantissas are explicitly listed. The exponents are implied by a linear
// expression with slope 217706.0/65536.0 ≈ log(10)/log(2).
//
// The table was generated by
// https://github.com/google/wuffs/blob/ba3818cb6b473a2ed0b38ecfc07dbbd3a97e8ae7/script/print-mpb-powers-of-10.go

union QuantizationDetails {
  CustomQuantization,
}

// Parameters for converting a quantized tensor back to float.
table QuantizationParameters {
  // These four parameters are the asymmetric linear quantization parameters.
  // Given a quantized value q, the corresponding float value f should be:
  //   f = scale * (q - zero_point)
  // For other quantization types, the QuantizationDetails below is used.

# does not run on Windows nodes.
#
# Note: This step is O(#nodes^2) as we check if each node is present in the list of succeeded nodes.
# Making it linear would add code complexity without much benefit (as it just takes ~1s for 5k nodes).
# Assumes:
#   NODE_NAMES
# Sets:
#   NON_LOGEXPORTED_NODES
function find_non_logexported_nodes() {

// returns [ErrUnknownPC]. In this case, *entry and the final seek
// position are unspecified.
//
// Note that DWARF line tables only permit sequential, forward scans.
// Hence, in the worst case, this takes time linear in the size of the
// line table. If the caller wishes to do repeated fast PC lookups, it
// should build an appropriate index of the line table.
func (r *LineReader) SeekPC(pc uint64, entry *LineEntry) error {

	if cheaprand()&uint32(oldC.Mask) != 0 {
		// As cache gets larger, choose to update it less often
		// so we can amortize the cost of building a new cache
		// (that cost is linear in oldc.Mask).
		return case_, tab
	}

	// Make a new cache.
	newC := buildInterfaceSwitchCache(oldC, t, case_, tab)

	// Update cache. Use compare-and-swap so if multiple threads

		// trying to move.
		// Look for volatile source, copy it to temporary before we check
		// the write barrier flag.
		// It is unlikely to have more than one of them. Just do a linear
		// search instead of using a map.
		// See issue 15854.
		type volatileCopy struct {
			src *Value // address of original volatile value
			tmp *Value // address of temporary we've copied the volatile value into

      }
      return false;
    }

    @Override
    public int hashCode() {
      return Arrays.hashCode(functions);
    }
  }

  /**
   * Linear CongruentialGenerator to use for consistent hashing. See
   * http://en.wikipedia.org/wiki/Linear_congruential_generator
   */
  private static final class LinearCongruentialGenerator {
    private long state;

 *       {@link #poll} and {@link #remove()}) run in {@code O(log n) time}.
 *   <li>The {@link #remove(Object)} and {@link #contains} operations require linear ({@code O(n)})
 *       time.
 *   <li>If you only access one end of the queue, and don't use a maximum size, this class is
 *       functionally equivalent to {@link PriorityQueue}, but significantly slower.
 * </ul>
 *

  private static final int CUTOFF = (int) (MAX_TABLE_SIZE * DESIRED_LOAD_FACTOR);

  /**
   * Returns an array size suitable for the backing array of a hash table that uses open addressing
   * with linear probing in its implementation. The returned size is the smallest power of two that
   * can hold setSize elements with the desired load factor. Always returns at least setSize + 2.
   */