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Han Wang
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add atom parameter, add unit tests
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14 files changed

+387
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examples/fparam/data/.gitignore

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*raw
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*.raw
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convert_aparam.py
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examples/fparam/train/input.json

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{
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"_comment": " model parameters",
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"model" : {
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"data_stat_nbatch": 1,
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"descriptor": {
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"type": "se_a",
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"sel": [60],
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{
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"_comment": " model parameters",
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"model" : {
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"data_stat_nbatch": 1,
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"descriptor": {
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"type": "se_a",
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"sel": [60],
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"rcut_smth": 1.80,
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"rcut": 6.00,
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"neuron": [25, 50, 100],
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"resnet_dt": false,
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"axis_neuron": 8,
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"seed": 1
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},
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"fitting_net" : {
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"neuron": [120, 120, 120],
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"resnet_dt": true,
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"numb_aparam": 1,
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"seed": 1
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}
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},
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"loss" : {
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"start_pref_e": 0.02,
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"limit_pref_e": 1,
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"start_pref_f": 1000,
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"limit_pref_f": 1,
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"start_pref_v": 0,
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"limit_pref_v": 0
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},
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"learning_rate" : {
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"start_lr": 0.001,
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"decay_steps": 5000,
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"decay_rate": 0.95
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},
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"_comment": " traing controls",
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"training" : {
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"systems": ["../data/e3000_i2000/", "../data/e8000_i2000/"],
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"set_prefix": "set",
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"stop_batch": 1000000,
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"batch_size": 1,
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"seed": 1,
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"_comment": " display and restart",
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"_comment": " frequencies counted in batch",
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"disp_file": "lcurve.out",
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"disp_freq": 100,
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"numb_test": 10,
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"save_freq": 1000,
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"save_ckpt": "model.ckpt",
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"load_ckpt": "model.ckpt",
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"disp_training":true,
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"time_training":true,
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"profiling": false,
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"profiling_file": "timeline.json"
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},
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"_comment": "that's all"
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}
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source/tests/common.py

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sys.data['forces'] = np.zeros([nframes,natoms,3])
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sys.to_deepmd_npy('system', prec=np.float64)
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np.save('system/set.000/fparam.npy', tmpdata.fparam)
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np.save('system/set.000/aparam.npy', tmpdata.aparam.reshape([nframes, natoms, 2]))
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class Data():
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def __init__ (self,
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np.random.seed(seed)
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self.coord += rand_pert * np.random.random(self.coord.shape)
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self.fparam = np.array([[0.1, 0.2]])
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self.aparam = np.tile(self.fparam, [1, 6])
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self.atype = np.array([0, 1, 1, 0, 1, 1], dtype = int)
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self.cell = 20 * np.eye(3)
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self.nframes = 1

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