fix: support headless rollout on remote training hosts

roboimi/demos/vla_scripts/eval_vla.py

@@ -37,6 +37,17 @@ if not OmegaConf.has_resolver("len"):
     OmegaConf.register_new_resolver("len", lambda x: len(x))
 
 
+def _configure_headless_mujoco_gl(eval_cfg: DictConfig) -> None:
+    if not bool(eval_cfg.get('headless', False)):
+        return
+    if os.environ.get('MUJOCO_GL'):
+        return
+    if os.environ.get('DISPLAY'):
+        return
+    os.environ['MUJOCO_GL'] = 'egl'
+    log.info('headless eval detected without DISPLAY; set MUJOCO_GL=egl')
+
+
 def load_checkpoint(
     ckpt_path: str,
     agent_cfg: DictConfig,
@@ -501,6 +512,7 @@ def _run_eval(cfg: DictConfig):
     print("=" * 80)
 
     eval_cfg = cfg.eval
+    _configure_headless_mujoco_gl(eval_cfg)
     device = eval_cfg.device
     camera_names = list(eval_cfg.camera_names)
     artifact_paths = _resolve_artifact_paths(eval_cfg)

roboimi/demos/vla_scripts/train_vla.py

@@ -76,6 +76,18 @@ if not OmegaConf.has_resolver("len"):
     OmegaConf.register_new_resolver("len", lambda x: len(x))
 
 
+def _resolve_run_output_dir() -> Path:
+    try:
+        from hydra.core.hydra_config import HydraConfig
+        if HydraConfig.initialized():
+            output_dir = HydraConfig.get().runtime.output_dir
+            if output_dir:
+                return Path(output_dir).resolve()
+    except Exception:
+        pass
+    return Path.cwd().resolve()
+
+
 _maybe_reexec_without_problematic_ld_preload()
 
 
@@ -319,8 +331,9 @@ def _run_training(cfg: DictConfig):
     swanlab_module = _init_swanlab(cfg)
     try:
         # 创建检查点目录
-        checkpoint_dir = Path("checkpoints")
+        run_output_dir = _resolve_run_output_dir()
-        checkpoint_dir.mkdir(exist_ok=True)
+        checkpoint_dir = run_output_dir / "checkpoints"
+        checkpoint_dir.mkdir(parents=True, exist_ok=True)
         default_best_model_path = checkpoint_dir / "vla_model_best.pt"
 
         # =========================================================================

tests/test_eval_vla_headless.py

@@ -90,6 +90,18 @@ class _FakeRenderer:
 
 
 class EvalVLAHeadlessTest(unittest.TestCase):
+    def test_headless_eval_sets_mujoco_gl_to_egl_when_display_missing(self):
+        cfg = OmegaConf.create({"eval": {"headless": True}})
+        with mock.patch.dict(eval_vla.os.environ, {}, clear=True):
+            eval_vla._configure_headless_mujoco_gl(cfg.eval)
+            self.assertEqual(eval_vla.os.environ.get("MUJOCO_GL"), "egl")
+
+    def test_headless_eval_preserves_existing_mujoco_gl(self):
+        cfg = OmegaConf.create({"eval": {"headless": True}})
+        with mock.patch.dict(eval_vla.os.environ, {"MUJOCO_GL": "osmesa"}, clear=True):
+            eval_vla._configure_headless_mujoco_gl(cfg.eval)
+            self.assertEqual(eval_vla.os.environ.get("MUJOCO_GL"), "osmesa")
+
     def test_eval_config_exposes_headless_default(self):
         eval_cfg = OmegaConf.load(Path("roboimi/vla/conf/eval/eval.yaml"))
 

tests/test_train_vla_transformer_optimizer.py

@@ -246,6 +246,35 @@ class TrainVLATransformerOptimizerTest(unittest.TestCase):
             module.torch.backends.cudnn.enabled = original
 
 
+    def test_resolve_run_output_dir_prefers_hydra_runtime_output_dir(self):
+        module = self._load_train_vla_module()
+        hydra_core_module = types.ModuleType('hydra.core')
+        hydra_hydra_config_module = types.ModuleType('hydra.core.hydra_config')
+
+        class _Runtime:
+            output_dir = '/tmp/hydra-output'
+
+        class _Cfg:
+            runtime = _Runtime()
+
+        class HydraConfigStub:
+            @staticmethod
+            def initialized():
+                return True
+            @staticmethod
+            def get():
+                return _Cfg()
+
+        hydra_hydra_config_module.HydraConfig = HydraConfigStub
+        with mock.patch.dict(sys.modules, {
+            'hydra.core': hydra_core_module,
+            'hydra.core.hydra_config': hydra_hydra_config_module,
+        }):
+            output_dir = module._resolve_run_output_dir()
+
+        self.assertEqual(Path(output_dir).resolve(), Path('/tmp/hydra-output').resolve())
+
+
     def test_train_script_uses_file_based_repo_root_on_sys_path(self):
         module = self._load_train_vla_module()