[Code scan] Make RunLmpHDF5 return the trajectory type it declares

[njzjz]

Found by Codex global repository scan of deepmodeling/dpgen2 at commit 2679611a3704f5c2646c8cb353e34177518db758.

RunLmpHDF5 changes the output signature for traj and model_devi to Artifact(HDF5Datasets):

dpgen2/dpgen2/op/run_lmp.py

Lines 405 to 414 in 2679611

	class RunLmpHDF5(RunLmp):
	@classmethod
	def get_output_sign(cls):
	output_sign = super().get_output_sign()
	output_sign["traj"] = Artifact(HDF5Datasets)
	output_sign["model_devi"] = Artifact(HDF5Datasets)
	return output_sign
	def get_model_devi(self, model_devi_file):
	return np.loadtxt(model_devi_file)

The inherited execute method still returns a filesystem path for traj:

dpgen2/dpgen2/op/run_lmp.py

Lines 203 to 207 in 2679611

	ret_dict = {
	"log": work_dir / lmp_log_name,
	"traj": work_dir / lmp_traj_name,
	"model_devi": self.get_model_devi(work_dir / lmp_model_devi_name),
	}

Only model_devi is converted by overriding get_model_devi; the trajectory remains work_dir / lmp_traj_name. This creates a signature/serialization contract mismatch for use_hdf5 LAMMPS runs and can break downstream consumers that receive HDF5 datasets.

Suggested fix: either convert trajectory output to the declared HDF5 dataset type, or keep the trajectory signature as Artifact(Path) until HDF5 trajectory support is implemented. Add a test for RunLmpHDF5.execute output types.