}) {
			t.Errorf("Contents not sorted")
		}
		for i := range xl.versions {
			hdr := xl.versions[i].header
			ver, err := xl.getIdx(i)
			if err != nil {
				t.Error(err)
				continue
			}
			gotHdr := ver.header()
			if hdr != gotHdr {
				t.Errorf("Header does not match, index: %+v != meta: %+v", hdr, gotHdr)
			}
		}
	}
	t.Run("load-legacy", func(t *testing.T) {

  // fully defined will avoid querying the shapes of the underlying
  // TensorHandles when ParallelTensor::Shape is called. This allows async
  // computation to continue without blocking.
  //
  // The return status and value is the same as `Execute`.
  absl::optional<std::vector<std::unique_ptr<ParallelTensor>>> Join(
      const std::vector<PartialTensorShape>& expected_output_shapes,

			objectInfos = append(objectInfos, obj)
			continue
		}

		// NoncurrentDays not passed yet.
		if time.Now().UTC().Before(lifecycle.ExpectedExpiryTime(obj.SuccessorModTime, event.NoncurrentDays)) {
			// add this version back to remaining versions for
			// subsequent lifecycle policy applications
			objectInfos = append(objectInfos, obj)
			continue
		}

		toDel = append(toDel, ObjectToDelete{

				hdr, err = tr.Next()
				if err != nil {
					if err == io.EOF {
						err = nil // Expected error
					}
					break
				}
				hdrs = append(hdrs, hdr)

				if v.chksums == nil {
					continue
				}
				h := crc32.NewIEEE()
				_, err = io.CopyBuffer(h, tr, rdbuf) // Effectively an incremental read
				if err != nil {
					break
				}
				chksums = append(chksums, fmt.Sprintf("%x", h.Sum(nil)))

func invertSparseEntries(src []sparseEntry, size int64) []sparseEntry {
	dst := src[:0]
	var pre sparseEntry
	for _, cur := range src {
		if cur.Length == 0 {
			continue // Skip empty fragments
		}
		pre.Length = cur.Offset - pre.Offset
		if pre.Length > 0 {
			dst = append(dst, pre) // Only add non-empty fragments
		}
		pre.Offset = cur.endOffset()
	}

      continue;
    }
    auto tag = tensorflow::strings::StrCat("Device #", i, " (", name, ")");
    // Copy to device
    TFE_TensorHandle* hdevice =
        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }

      return 0;
    }

    outer:
    for (int i = 0; i < array.length - target.length + 1; i++) {
      for (int j = 0; j < target.length; j++) {
        if (array[i + j] != target[j]) {
          continue outer;
        }
      }
      return i;
    }
    return -1;
  }

  /**
   * Returns the index of the last appearance of the value {@code target} in {@code array}.
   *

            StackTraceElement se = stackTrace[ i ];

            if ( i == s && SmbTreeImpl.class.getName().equals(se.getClassName()) && "close".equals(se.getMethodName()) ) {
                s++;
                continue;
            }

            if ( se.getClassName().startsWith("org.junit.runners.") ) {
                e = i - 4;
                break;
            }
        }

      return 0;
    }

    outer:
    for (int i = 0; i < array.length - target.length + 1; i++) {
      for (int j = 0; j < target.length; j++) {
        if (array[i + j] != target[j]) {
          continue outer;
        }
      }
      return i;
    }
    return -1;
  }

  /**
   * Returns the index of the last appearance of the value {@code target} in {@code array}.
   *

    per_device_output_tensors.push_back(device_thread->Join(status));
    // We will run every Join even if there are bad statuses in case the user
    // wants to recover and continue running ops on the parallel device (which
    // would otherwise deadlock).
    if (TF_GetCode(status) != TF_OK &&
        (first_bad_status == nullptr