[Code scan] Pass type_map to dpdata when preparing FP tasks

[njzjz]

This issue is a result of a Codex global code scan of deepmodeling/fpop at commit b05b337590c31a5237b2dcbd9c0833b841c08cd4.

Relevant code:

fpop/fpop/prep_fp.py

Lines 121 to 141 in b05b337

	inputs = op_in['inputs']
	confs = op_in['confs']
	type_map = op_in['type_map']
	prepare_image_config = op_in["prep_image_config"]
	optional_artifact = op_in["optional_artifact"]
	optional_input = op_in["optional_input"]
	try:
	conf_format = optional_input["conf_format"]
	except:
	conf_format = "deepmd/npy"
	task_names = []
	task_paths = []
	#System
	counter = 0
	# loop over list of System
	for system in confs:
	ss = dpdata.System(system, fmt=conf_format, labeled=False)
	for ff in range(ss.get_nframes()):
	nn, pp = self._exec_one_frame(counter, inputs, ss[ff], prepare_image_config, optional_input, optional_artifact)

fpop/fpop/vasp.py

Lines 90 to 98 in b05b337

	for nn in atom_names:
	potcar_contents.append(self._potcars[nn])
	return "".join(potcar_contents)
	def make_kpoints(
	self,
	box : np.ndarray,
	) -> str:
	return make_kspacing_kpoints(box, self.kspacing, self.kgamma)

Problem:
PrepFp.execute() reads type_map from op_in, but the value is never passed to dpdata.System(...). For deepmd/npy inputs that contain type.raw but do not contain type_map.raw, dpdata loads atom names as synthetic names such as Type_0 and Type_1.

That breaks downstream preparation. For example, VASP POTCAR generation indexes the pseudopotential map by atom_names, so VaspInputs.make_potcar() can raise KeyError: 'Type_0' even though the workflow input provided type_map=["H", "O"].

Minimal reproduction:

s1 = dpdata.System(root, fmt="deepmd/npy", labeled=False)
print(s1["atom_names"])
# ['Type_0', 'Type_1']

s2 = dpdata.System(root, fmt="deepmd/npy", labeled=False, type_map=["H", "O"])
print(s2["atom_names"])
# ['H', 'O']

Expected behavior:
PrepFp.execute() should preserve the workflow-provided type_map when loading configurations, or otherwise map dpdata's synthetic names before calling backend-specific prep_task() implementations.