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Unverified Commit 06cdce78 authored by Farhad Ramezanghorbani's avatar Farhad Ramezanghorbani Committed by GitHub
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get AEV dimension from aev_computer (#442)

parent 62eb2236
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Showing with 10 additions and 8 deletions
examples/nnp_training.py
View file @ 06cdce78
......@@ -92,9 +92,10 @@ print('Self atomic energies: ', energy_shifter.self_energies)
#
###############################################################################
# Now let's define atomic neural networks.
aev_dim = aev_computer.aev_length
H_network = torch.nn.Sequential(
torch.nn.Linear(384, 160),
torch.nn.Linear(aev_dim, 160),
torch.nn.CELU(0.1),
torch.nn.Linear(160, 128),
torch.nn.CELU(0.1),
......@@ -104,7 +105,7 @@ H_network = torch.nn.Sequential(
)
C_network = torch.nn.Sequential(
torch.nn.Linear(384, 144),
torch.nn.Linear(aev_dim, 144),
torch.nn.CELU(0.1),
torch.nn.Linear(144, 112),
torch.nn.CELU(0.1),
......@@ -114,7 +115,7 @@ C_network = torch.nn.Sequential(
)
N_network = torch.nn.Sequential(
torch.nn.Linear(384, 128),
torch.nn.Linear(aev_dim, 128),
torch.nn.CELU(0.1),
torch.nn.Linear(128, 112),
torch.nn.CELU(0.1),
......@@ -124,7 +125,7 @@ N_network = torch.nn.Sequential(
)
O_network = torch.nn.Sequential(
torch.nn.Linear(384, 128),
torch.nn.Linear(aev_dim, 128),
torch.nn.CELU(0.1),
torch.nn.Linear(128, 112),
torch.nn.CELU(0.1),
......
examples/nnp_training_force.py
View file @ 06cdce78
......@@ -57,9 +57,10 @@ print('Self atomic energies: ', energy_shifter.self_energies)
###############################################################################
# The code to define networks, optimizers, are mostly the same
aev_dim = aev_computer.aev_length
H_network = torch.nn.Sequential(
torch.nn.Linear(384, 160),
torch.nn.Linear(aev_dim, 160),
torch.nn.CELU(0.1),
torch.nn.Linear(160, 128),
torch.nn.CELU(0.1),
......@@ -69,7 +70,7 @@ H_network = torch.nn.Sequential(
)
C_network = torch.nn.Sequential(
torch.nn.Linear(384, 144),
torch.nn.Linear(aev_dim, 144),
torch.nn.CELU(0.1),
torch.nn.Linear(144, 112),
torch.nn.CELU(0.1),
......@@ -79,7 +80,7 @@ C_network = torch.nn.Sequential(
)
N_network = torch.nn.Sequential(
torch.nn.Linear(384, 128),
torch.nn.Linear(aev_dim, 128),
torch.nn.CELU(0.1),
torch.nn.Linear(128, 112),
torch.nn.CELU(0.1),
......@@ -89,7 +90,7 @@ N_network = torch.nn.Sequential(
)
O_network = torch.nn.Sequential(
torch.nn.Linear(384, 128),
torch.nn.Linear(aev_dim, 128),
torch.nn.CELU(0.1),
torch.nn.Linear(128, 112),
torch.nn.CELU(0.1),
......
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