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Remove torch.unique for finding the maximum three body index and little cleanup in united tests #161

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merged 13 commits into from
Sep 5, 2023
Merged

Remove torch.unique for finding the maximum three body index and little cleanup in united tests #161

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ccad860
Optimize the Atoms2Graph and fixed the np.meshgrid
kenko911 Aug 29, 2023
bafbc16
put unittests
kenko911 Aug 29, 2023
120a36e
Merge branch 'materialsvirtuallab:main' into main
kenko911 Aug 29, 2023
9e1a24b
improve the _three_body.py and test_M3GNetCalculator in test_ase.py
kenko911 Aug 29, 2023
1057435
Merge branch 'main' into main
shyuep Aug 29, 2023
a65b926
Merge branch 'materialsvirtuallab:main' into main
kenko911 Aug 31, 2023
83b8eb8
add cpu() in ase.py and compute.py to enable the GPU usage for MatGL-…
kenko911 Aug 31, 2023
184c0ec
Merge branch 'materialsvirtuallab:main' into main
kenko911 Aug 31, 2023
7db50e7
included the unit-test for hessian test_ase.py to improve the coverag…
kenko911 Sep 1, 2023
5b3ea43
Merge branch 'main' of https://github.com/kenko911/matgl
kenko911 Sep 1, 2023
517ba07
Merge branch 'materialsvirtuallab:main' into main
kenko911 Sep 3, 2023
8d2e6ef
Merge branch 'materialsvirtuallab:main' into main
kenko911 Sep 5, 2023
1253ba5
remove reducdant torch.unique for finding the maximum three_body inde…
kenko911 Sep 5, 2023
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2 changes: 1 addition & 1 deletion matgl/graph/compute.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@ def compute_3body(g: dgl.DGLGraph):
src_id = torch.tensor(triple_bond_indices[:, 0], dtype=matgl.int_th)
dst_id = torch.tensor(triple_bond_indices[:, 1], dtype=matgl.int_th)
l_g = dgl.graph((src_id, dst_id))
three_body_id = torch.unique(torch.concatenate(l_g.edges()))
three_body_id = torch.concatenate(l_g.edges())
n_triple_ij = torch.tensor(n_triple_ij, dtype=matgl.int_th)
max_three_body_id = torch.max(three_body_id) + 1 if three_body_id.numel() > 0 else 0
l_g.ndata["bond_dist"] = g.edata["bond_dist"][:max_three_body_id]
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2 changes: 1 addition & 1 deletion matgl/models/_m3gnet.py
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Expand Up @@ -238,7 +238,7 @@ def forward(
l_g.ndata["bond_dist"] = g.edata["bond_dist"][valid_three_body]
l_g.ndata["pbc_offset"] = g.edata["pbc_offset"][valid_three_body]
else:
three_body_id = torch.unique(torch.concatenate(l_g.edges()))
three_body_id = torch.concatenate(l_g.edges())
max_three_body_id = torch.max(three_body_id) + 1 if three_body_id.numel() > 0 else 0
l_g.ndata["bond_vec"] = g.edata["bond_vec"][:max_three_body_id]
l_g.ndata["bond_dist"] = g.edata["bond_dist"][:max_three_body_id]
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14 changes: 1 addition & 13 deletions tests/layers/test_graph_conv.py
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Expand Up @@ -6,11 +6,7 @@
import torch
from torch import nn

from matgl.graph.compute import (
compute_theta_and_phi,
create_line_graph,
)
from matgl.layers import BondExpansion, EmbeddingBlock, SphericalBesselWithHarmonics
from matgl.layers import BondExpansion, EmbeddingBlock
from matgl.layers._graph_convolution import (
MLP,
M3GNetBlock,
Expand Down Expand Up @@ -88,10 +84,6 @@ def test_m3gnet_graph_conv(self, graph_MoS):
bond_expansion = BondExpansion(max_l=3, max_n=3, cutoff=5.0, rbf_type="SphericalBessel", smooth=False)
bond_basis = bond_expansion(bond_dist)
g1.edata["rbf"] = bond_basis
sb_and_sh = SphericalBesselWithHarmonics(max_n=3, max_l=3, cutoff=5.0, use_smooth=False, use_phi=False)
l_g1 = create_line_graph(g1, threebody_cutoff=4.0)
l_g1.apply_edges(compute_theta_and_phi)
sb_and_sh(l_g1)
max_n = 3
max_l = 3
num_node_feats = 16
Expand Down Expand Up @@ -137,10 +129,6 @@ def test_m3gnet_block(self, graph_MoS):
bond_expansion = BondExpansion(max_l=3, max_n=3, cutoff=5.0, rbf_type="SphericalBessel", smooth=False)
bond_basis = bond_expansion(g1.edata["bond_dist"])
g1.edata["rbf"] = bond_basis
sb_and_sh = SphericalBesselWithHarmonics(max_n=3, max_l=3, cutoff=5.0, use_smooth=False, use_phi=False)
l_g1 = create_line_graph(g1, threebody_cutoff=4.0)
l_g1.apply_edges(compute_theta_and_phi)
sb_and_sh(l_g1)
num_node_feats = 16
num_edge_feats = 32
num_state_feats = 64
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