return oi, InvalidPart{
					PartNumber: part.PartNumber,
				}
			}
			wantCS := map[string]string{
				hash.ChecksumCRC32.String():  part.ChecksumCRC32,
				hash.ChecksumCRC32C.String(): part.ChecksumCRC32C,
				hash.ChecksumSHA1.String():   part.ChecksumSHA1,
				hash.ChecksumSHA256.String(): part.ChecksumSHA256,
			}
			if wantCS[checksumType.String()] != crc {
				return oi, InvalidPart{

   * exists, a CAS is tried.  Retries proceed by "double hashing",
   * using a secondary hash (Marsaglia XorShift) to try to find a
   * free slot.
   *
   * The table size is capped because, when there are more threads
   * than CPUs, supposing that each thread were bound to a CPU,
   * there would exist a perfect hash function mapping threads to
   * slots that eliminates collisions. When we reach capacity, we

 * amortized) constant time operations. Expected in the hashtable sense (depends on the hash
 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>As compared with {@link java.util.LinkedHashMap}, this structure places significantly reduced

				if err != nil {
					err = msgp.WrapError(err, "Algorithm")
					return
				}
				z.Algorithm = BitrotAlgorithm(zb0002)
			}
		case "Hash":
			z.Hash, err = dc.ReadBytes(z.Hash)
			if err != nil {
				err = msgp.WrapError(err, "Hash")
				return
			}
		default:
			err = dc.Skip()
			if err != nil {
				err = msgp.WrapError(err)
				return
			}
		}
	}
	return
}

  public void testCreateFromHashMultimap() {
    Multimap<Double, Double> hash = HashMultimap.create();
    hash.put(1.0, 2.0);
    hash.put(2.0, 3.0);
    hash.put(3.0, 4.0);
    hash.put(4.0, 5.0);

    TreeMultimap<Double, Double> copyFromHash = TreeMultimap.create(hash);
    assertEquals(hash, copyFromHash);
    assertEquals(Ordering.natural(), copyFromHash.keyComparator());

    /**
     * Checks the whole hash table for poor hash distribution. Takes O(n) in the worst case, O(n /
     * log n) on average.
     *
     * <p>The online hash flooding detecting in RegularSetBuilderImpl.add can detect e.g. many
     * exactly matching hash codes, which would cause construction to take O(n^2), but can't detect

		}
	}

	checksumType := hash.NewChecksumType(r.Header.Get(xhttp.AmzChecksumAlgo))
	if checksumType.Is(hash.ChecksumInvalid) {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrInvalidRequestParameter), r.URL)
		return
	} else if checksumType.IsSet() && !checksumType.Is(hash.ChecksumTrailing) {
		opts.WantChecksum = &hash.Checksum{Type: checksumType}
	}

			}
			if !bytes.Equal(unMarshalXLMeta.Erasure.Checksums[i].Hash, jsoniterXLMeta.Erasure.Checksums[i].Hash) {
				t.Errorf("Expected the Erasure Checksum Hash to be \"%s\", got \"%s\".", unMarshalXLMeta.Erasure.Checksums[i].Hash, jsoniterXLMeta.Erasure.Checksums[i].Hash)
			}
		}
	}

	if unMarshalXLMeta.Minio.Release != jsoniterXLMeta.Minio.Release {

  }

  /**
   * Computes the hash code of the {@code file} using {@code hashFunction}.
   *
   * @param file the file to read
   * @param hashFunction the hash function to use to hash the data
   * @return the {@link HashCode} of all of the bytes in the file
   * @throws IOException if an I/O error occurs
   * @since 12.0
   * @deprecated Prefer {@code asByteSource(file).hash(hashFunction)}.
   */
  @Deprecated

    control_output_nodes.push_back(&control_outputs[i]->node);
  }

  // Do the actual function creation.
  DCHECK(append_hash_to_fn_name <= 1);
  tensorflow::FunctionDef fdef;
  status->status = tensorflow::GraphToFunctionDef(
      fn_body->graph, fn_name, append_hash_to_fn_name != 0,
      /*set_stateful_from_nodes=*/true,
      /*copy_placeholder_attrs_from_nodes=*/true, body_nodes, input_tensors,