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weekend run with prim as cluster_type in training

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Si11ium 2020-06-26 18:35:47 +02:00
parent 84c879e5bf
commit bd02773472
1 changed files with 7 additions and 3 deletions
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10
multi_run.py
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@ -17,13 +17,17 @@ if __name__ == '__main__':
config = ThisConfig().read_namespace(args) config = ThisConfig().read_namespace(args)
# bias, activation, model, norm, max_epochs # bias, activation, model, norm, max_epochs
pn2 = dict(model_type='PN2', model_use_bias=True, model_use_norm=True, data_batchsize=250) pn2 = dict(model_type='PN2', model_use_bias=True, model_use_norm=True, data_batchsize=250)
# p2g = dict(model_type='P2G', model_use_bias=True, model_use_norm=True, data_batchsize=250) # p2g = dict(model_type='P2G', model_use_bias=True, model_use_norm=True, data_batchsize=250)
# bias, activation, model, norm, max_epochs # bias, activation, model, norm, max_epochs
for arg_dict in [pn2]: for arg_dict in [pn2]:
for seed in range(2): for seed in range(2):
arg_dict.update(main_seed=seed) for poly_as_plane in [True, False]:
for normals_as_cords in [True, False]:
arg_dict.update(main_seed=seed,
normals_as_cords=normals_as_cords, poly_as_plane=poly_as_plane)
config = config.update(arg_dict) config = config.update(arg_dict)
run_lightning_loop(config) run_lightning_loop(config)