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input.json
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input.json
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{
"_comment1": "that's all",
"model": {
"type_map": [
"O",
"H"
],
"descriptor": {
"type": "se_e2_a",
"sel": [
46,
92
],
"rcut_smth": 0.5,
"rcut": 6.0,
"neuron": [
25,
50,
100
],
"resnet_dt": false,
"axis_neuron": 16,
"precision": "float64",
"seed": 1,
"_comment2": " that's all"
},
"fitting_net_dict": {
"water_dipole": {
"type": "dipole",
"sel_type": [
0
],
"neuron": [
100,
100,
100
],
"resnet_dt": true,
"precision": "float64",
"seed": 1,
"_comment3": " that's all"
},
"water_ener": {
"neuron": [
240,
240,
240
],
"resnet_dt": true,
"precision": "float64",
"seed": 1,
"_comment4": " that's all"
}
},
"_comment5": " that's all"
},
"learning_rate": {
"type": "exp",
"decay_steps": 5000,
"start_lr": 0.001,
"stop_lr": 3.51e-08,
"_comment6": "that's all"
},
"loss_dict": {
"water_dipole": {
"type": "tensor",
"pref": 1.0,
"pref_atomic": 1.0,
"_comment7": " that's all"
},
"water_ener": {
"type": "ener",
"start_pref_e": 0.02,
"limit_pref_e": 1,
"start_pref_f": 1000,
"limit_pref_f": 1,
"start_pref_v": 0,
"limit_pref_v": 0,
"_comment8": " that's all"
}
},
"training": {
"data_dict": {
"water_dipole": {
"training_data": {
"systems": [
"../../water_tensor/dipole/training_data/atomic_system",
"../../water_tensor/dipole/training_data/global_system"
],
"batch_size": "auto",
"_comment9": "that's all"
},
"validation_data": {
"systems": [
"../../water_tensor/dipole/validation_data/atomic_system",
"../../water_tensor/dipole/validation_data/global_system"
],
"batch_size": 1,
"numb_btch": 3,
"_comment10": "that's all"
}
},
"water_ener": {
"training_data": {
"systems": [
"../../water/data/data_0/",
"../../water/data/data_1/",
"../../water/data/data_2/"
],
"batch_size": "auto",
"_comment11": "that's all"
},
"validation_data": {
"systems": [
"../../water/data/data_3/"
],
"batch_size": 1,
"numb_btch": 3,
"_comment12": "that's all"
}
}
},
"fitting_weight": {
"water_dipole": 10,
"water_ener": 20
},
"numb_steps": 1000000,
"seed": 10,
"disp_file": "lcurve.out",
"disp_freq": 100,
"save_freq": 1000,
"_comment13": "that's all"
}
}