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Assign device for calculating minimum distances as GPU, if available. #43

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Assign device for calculating minimum distances as GPU, if available. #43

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9 changes: 2 additions & 7 deletions alframework/ml_interfaces/hippynn_interface.py
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Original file line number Diff line number Diff line change
Expand Up @@ -374,20 +374,15 @@ def train_HIPNN_model(model_dir,
arrays = database.arr_dict

arrays[species_key] = arrays[species_key].to(torch.int64) # or .long()

min_dists = hippynn.pretraining.calculate_min_dists(database.arr_dict,species_key,coordinates_key,6.0,cell_name=cell_key,batch_size=256)
min_dists_flag = min_dists>network_params["dist_soft_min"]
for curK in database.arr_dict.keys():
database.arr_dict[curK] = database.arr_dict[curK][min_dists_flag]


n_atoms = (
arrays[species_key] # tensor
.to(torch.bool) # cast to bool
.to(torch.int32) # or .int() / .to(torch.int64) as you prefer
.sum(dim=1) # sum along atom axis
)

min_dists = hippynn.pretraining.calculate_min_dists(database.arr_dict,species_name=species_key,positions_name=coordinates_key,dist_hard_max=6.0,cell_name=cell_key,batch_size=256)
min_dists = hippynn.pretraining.calculate_min_dists(database.arr_dict,species_name=species_key,positions_name=coordinates_key,dist_hard_max=6.0,cell_name=cell_key,batch_size=256,device=device_cuda)
min_dists_flag = min_dists>network_params["dist_soft_min"]
for curK in database.arr_dict.keys():
database.arr_dict[curK] = database.arr_dict[curK][min_dists_flag]
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