[BUG] Tensor Shape Mismatch During DeepMD Training

### Bug summary

When running DeepMD-kit, an error occurs related to a mismatch in tensor shapes. Specifically, the error message indicates that the shape of the input tensor does not match the expected shape, causing a ValueError during training data processing. This issue might be related to the configuration of the magnetic spin parameters in the input files and the corresponding training data.

I suspect the issue might be due to the training data generated from CP2K not containing magnetic spin data. This issue could stem from the fact that the example provided might include data derived from VASP's OSZICAR content, which contains spin data.

### DeePMD-kit Version

registry.dp.tech/dptech/deepmd-kit:2024Q1-d23cf3e

### Backend and its version

registry.dp.tech/dptech/deepmd-kit:2024Q1-d23cf3e

### How did you download the software?

Others (write below)

### Input Files, Running Commands, Error Log, etc.

Traceback (most recent call last):
File "/opt/mamba/bin/dp", line 8, in
sys.exit(main())
File "/opt/mamba/lib/python3.10/site-packages/deepmd/main.py", line 807, in main
deepmd_main(args)
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/entrypoints/main.py", line 72, in main
train_dp(**dict_args)
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/entrypoints/train.py", line 153, in train
_do_work(jdata, run_opt, is_compress)
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/entrypoints/train.py", line 265, in _do_work
model.build(train_data, stop_batch, origin_type_map=origin_type_map)
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/train/trainer.py", line 284, in build
self.model.data_stat(data)
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/model/ener.py", line 128, in data_stat
self._compute_input_stat(
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/model/ener.py", line 147, in _compute_input_stat
self.descrpt.compute_input_stats(
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/descriptor/se_a.py", line 373, in compute_input_stats
sysr, sysr2, sysa, sysa2, sysn = self._compute_dstats_sys_smth(
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/descriptor/se_a.py", line 841, in _compute_dstats_sys_smth
dd_all = run_sess(
File "/opt/mamba/lib/python3.10/site-packages/deepmd/tf/utils/sess.py", line 31, in run_sess
return sess.run(*args, **kwargs)
File "/opt/mamba/lib/python3.10/site-packages/tensorflow/python/client/session.py", line 972, in run
result = self._run(None, fetches, feed_dict, options_ptr,
File "/opt/mamba/lib/python3.10/site-packages/tensorflow/python/client/session.py", line 1189, in _run
raise ValueError(
ValueError: Cannot feed value of shape (6,) for Tensor d_sea_t_natoms:0, which has shape (7,)


### Steps to Reproduce

{
"model": {
"type_map": [
"C",
"O",
"H",
"S"
],
"descriptor": {
"type": "se_e2_a",
"sel": [
16,
46,
92,
52
],
"rcut_smth": 1.0,
"rcut": 5.0,
"neuron": [
25,
50,
100
],
"resnet_dt": false,
"axis_neuron": 16,
"seed": 930070626
},
"fitting_net": {
"neuron": [
240,
240,
240
],
"resnet_dt": true,
"seed": 3301444140
},
"spin": {
"use_spin": [
false,
false,
false,
true
],
"virtual_len": [
0.4
],
"spin_norm": [
0.0,
0.0,
0.0,
1.0
],
"_comment4": " that's all"
}
},
"learning_rate": {
"type": "exp",
"start_lr": 0.001,
"decay_steps": 10000
},
"loss": {
"type": "ener_spin",
"start_pref_e": 0.1,
"limit_pref_e": 2,
"start_pref_fr": 1000,
"limit_pref_fr": 1.0,
"start_pref_fm": 10000,
"limit_pref_fm": 10.0,
"start_pref_v": 0,
"limit_pref_v": 0,
"_comment7": " that's all"
},
"training": {
"stop_batch": 50000,
"disp_file": "lcurve.out",
"disp_freq": 500,
"numb_test": 1,
"save_freq": 500,
"save_ckpt": "model.ckpt",
"disp_training": true,
"time_training": true,
"profiling": false,
"profiling_file": "timeline.json",
"_comment": "that's all",
"training_data": {
"systems": [
"../data.init/init/final1/training_data",
"../data.init/init/final2/training_data",
"../data.init/init/final3/training_data",
"../data.iters/iter.000000/02.fp/data.000",
"../data.iters/iter.000000/02.fp/data.001",
"../data.iters/iter.000000/02.fp/data.002",
"../data.iters/iter.000001/02.fp/data.000",
"../data.iters/iter.000001/02.fp/data.001",
"../data.iters/iter.000001/02.fp/data.002",
"../data.iters/iter.000002/02.fp/data.000",
"../data.iters/iter.000002/02.fp/data.001",
"../data.iters/iter.000002/02.fp/data.002",
"../data.iters/iter.000003/02.fp/data.000",
"../data.iters/iter.000003/02.fp/data.001",
"../data.iters/iter.000003/02.fp/data.002",
"../data.iters/iter.000004/02.fp/data.000",
"../data.iters/iter.000004/02.fp/data.001",
"../data.iters/iter.000004/02.fp/data.002",
"../data.iters/iter.000005/02.fp/data.000",
"../data.iters/iter.000005/02.fp/data.001",
"../data.iters/iter.000005/02.fp/data.002",
"../data.iters/iter.000006/02.fp/data.000",
"../data.iters/iter.000006/02.fp/data.001",
"../data.iters/iter.000006/02.fp/data.002",
"../data.iters/iter.000007/02.fp/data.000",
"../data.iters/iter.000007/02.fp/data.001",
"../data.iters/iter.000007/02.fp/data.002",
"../data.iters/iter.000009/02.fp/data.000",
"../data.iters/iter.000010/02.fp/data.000",
"../data.iters/iter.000011/02.fp/data.000",
"../data.iters/iter.000011/02.fp/data.002",
"../data.iters/iter.000012/02.fp/data.000",
"../data.iters/iter.000012/02.fp/data.002",
"../data.iters/iter.000013/02.fp/data.000",
"../data.iters/iter.000013/02.fp/data.002",
"../data.iters/iter.000014/02.fp/data.000",
"../data.iters/iter.000014/02.fp/data.002",
"../data.iters/iter.000015/02.fp/data.000",
"../data.iters/iter.000015/02.fp/data.002",
"../data.iters/iter.000016/02.fp/data.000",
"../data.iters/iter.000016/02.fp/data.002",
"../data.iters/iter.000017/02.fp/data.000",
"../data.iters/iter.000017/02.fp/data.002",
"../data.iters/iter.000018/02.fp/data.000",
"../data.iters/iter.000018/02.fp/data.002",
"../data.iters/iter.000019/02.fp/data.000",
"../data.iters/iter.000019/02.fp/data.002",
"../data.iters/iter.000020/02.fp/data.000",
"../data.iters/iter.000020/02.fp/data.002",
"../data.iters/iter.000021/02.fp/data.000",
"../data.iters/iter.000021/02.fp/data.002",
"../data.iters/iter.000022/02.fp/data.000"
],
"batch_size": [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1
]
},
"seed": 2826335128
}
}

### Further Information, Files, and Links

_No response_