@Inject
    private Logger logger;

    @Inject
    private LegacySupport legacySupport;

    private void injectSession(ArtifactResolutionRequest request) {
        MavenSession session = legacySupport.getSession();

        if (session != null) {
            request.setOffline(session.isOffline());
            request.setForceUpdate(session.getRequest().isUpdateSnapshots());

    }
}
```

### 5.3 File Handle Integration
```java
// In SmbFile.java
@Override
protected void handleConnectionLoss(IOException error) {
    if (tree.getSession().isWitnessEnabled()) {
        log.info("Connection lost, waiting for witness notification before retry");
        
        // Wait briefly for witness notification before retrying
        try {

  Session* session;
  status->status = NewSession(opt->options, &session);
  if (status->status.ok()) {
    TF_Session* new_session = new TF_Session(session, graph);
    if (graph != nullptr) {
      mutex_lock l(graph->mu);
      graph->sessions[new_session] = "";
    }
    return new_session;
  } else {
    LOG(ERROR) << status->status;
    DCHECK_EQ(nullptr, session);
    return nullptr;
  }
}

+  char ut_host[UT_HOSTSIZE]
+    __attribute_nonstring__;	/* Hostname for remote login.  */
   struct exit_status ut_exit;	/* Exit status of a process marked
 				   as DEAD_PROCESS.  */
 /* The ut_session and ut_tv fields must be the same size when compiled
diff --git a/sysdeps/gnu/bits/utmpx.h b/sysdeps/gnu/bits/utmpx.h
index f8716ca..13d84e4 100644
--- a/sysdeps/gnu/bits/utmpx.h
+++ b/sysdeps/gnu/bits/utmpx.h

                req.setShareAccess(sharing);
                req.setFileAttributes(attrs);

                // Add SMB3 features support with error handling for compatibility
                SmbSessionImpl session = h.getSession();

                // Enable lease support if available, with fallback for compatibility
                boolean leasesAdded = false;
                if (config.isUseLeases() && h.isSMB3()) {
                    try {

    *   symbolic tensors outside the scope of the model are used in custom loss
        functions. The flag can be disabled for these cases and ideally the
        usage pattern will need to be fixed.
    *   Mark Keras `set_session` as `compat.v1` only.
    *   `tf.keras.estimator.model_to_estimator` now supports exporting to
        `tf.train.Checkpoint format`, which allows the saved checkpoints to be
        compatible with `model.load_weights`.