}
	return r, err
}

// ReplicationState represents internal replication state
type ReplicationState struct {
	ReplicaTimeStamp          time.Time              // timestamp when last replica update was received
	ReplicaStatus             replication.StatusType // replica statusstringis
	DeleteMarker              bool                   // represents DeleteMarker replication state

  std::vector<const Tensor*> input_tensors_vector(num_inputs, nullptr);
  // A vector to keep track of newly created `tf::Tensor` objects.
  std::vector<Tensor> all_input_tensors;
  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {
    // Note that we take the address of the elements in `all_input_tensors`

	if debugPrint {
		fmt.Printf("grid: Queued Response %+v Side: %v\n", resp, c.side)
	}
	if err != nil {
		return err
	}
	t := time.Now().UTC()
	c.lastConnect.Store(&t)
	// Signal that we are reconnected, update state and handle messages.
	// Prevent other connections from connecting while we process.
	c.reconnectMu.Lock()
	if c.remoteID != nil {
		c.reconnected()
	}
	rid := uuid.UUID(req.ID)
	c.remoteID = &rid

#
# This file is autogenerated by pip-compile with Python 3.13
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.3.0 \
    --hash=sha256:9824a48b654a306168f63e0d97714665f8490b8d89ec7bf2efc24bf67cf579b3 \
    --hash=sha256:d96fda5c884f1b22178852f30ffa85766d50b99e00775ea626c23304f582fc4f
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

				continue
			}

			// Collect each new cred.ParentUser into parentUsers
			parentUserActualDNList = append(parentUserActualDNList, ldapActualDN)

			// Update the ldapUsernameMap
			actualDNToLDAPUsernameMap[ldapActualDN] = ldapUsername

			// Update the actualDNToParentUserMap
			actualDNToParentUserMap[ldapActualDN] = cred.ParentUser
		}

#
# This file is autogenerated by pip-compile with Python 3.10
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.12
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.12
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

				return sp
			}
			sp2 := formatSPD(spd, blk.GNU().Sparse())
			for len(sp2) > 0 {
				var spHdr block
				sp2 = formatSPD(sp2, spHdr.Sparse())
				spb = append(spb, spHdr[:]...)
			}

			// Update size fields in the header block.
			realSize := hdr.Size
			hdr.Size = 0 // Encoded size; does not account for encoded sparse map
			for _, s := range spd {
				hdr.Size += s.Length
			}

#
# This file is autogenerated by pip-compile with Python 3.9
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \