Summary
Currently, the linear model is implemented to combine multiple frozen models. However, this architecture can be further used for models with more complicated combining rules. I wonder if it is possible to have the design similar to multi-task/model/shared_dict and make all submodels share (some of) their parameters.
I would like to know the comments/suggestions from developers about this feature and the relevant code implementation. I can implement it once we come to a conclusion.
Thanks.
Detailed Description
An example input expected:
"model": {
"type": "custom_ener_model",
"shared_dict": {
"type_map_all": [
"O",
"H"
],
"sea_descriptor_1": {
"type": "se_e2_a",
"sel": [
46,
92
],
"rcut_smth": 0.50,
"rcut": 6.00,
"neuron": [
25,
50,
100
],
"resnet_dt": false,
"axis_neuron": 16,
"type_one_side": true,
"seed": 1,
"_comment": " that's all"
},
"_comment": "that's all"
},
"models": [
{
"type_map": "type_map_all",
"descriptor": "sea_descriptor_1",
"fitting_net" : {
"neuron": [240, 240, 240],
"resnet_dt": true,
"seed": 1
}
},
{
"type_map": "type_map_all",
"descriptor": "sea_descriptor_1",
"fitting_net" : {
"type": "dipole",
"neuron": [100, 100, 100],
"resnet_dt": true,
"seed": 1
}
}
],
"model_arg":{}
},Further Information, Files, and Links
No response
Summary
Currently, the linear model is implemented to combine multiple frozen models. However, this architecture can be further used for models with more complicated combining rules. I wonder if it is possible to have the design similar to
multi-task/model/shared_dictand make all submodels share (some of) their parameters.I would like to know the comments/suggestions from developers about this feature and the relevant code implementation. I can implement it once we come to a conclusion.
Thanks.
Detailed Description
An example input expected:
Further Information, Files, and Links
No response