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Implement representation block of DimNet++ #290

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Implement representation block of DimNet++ #290

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0e0d751
initial skeleton implementation of dim(e)netpp. uses a lot of placeho…
AnnaPicha Oct 18, 2024
482a455
Merge branch 'main' into dev-dimenetpp
wiederm Oct 20, 2024
12c5680
Merge branch 'main' into dev-dimenetpp
wiederm Oct 20, 2024
1d1c25b
representation modules
wiederm Oct 20, 2024
99b535f
small bugfixes
AnnaPicha Oct 21, 2024
ed54bc8
update representaiton block
wiederm Oct 21, 2024
e746018
dummy angular
wiederm Oct 23, 2024
02f3e7a
changes in envelope test function
AnnaPicha Oct 23, 2024
f762f22
Merge branch 'dev-dimenetpp' of https://github.com/choderalab/modelfo…
AnnaPicha Oct 23, 2024
d032727
notes on the envelope function
wiederm Oct 23, 2024
97b7e9d
Added comments in the BesselBasisLayer
AnnaPicha Oct 24, 2024
8ca66dd
Merge branch 'main' into dev-dimenetpp
wiederm Oct 25, 2024
e46e530
Merge branch 'main' into dev-dimenetpp
wiederm Oct 30, 2024
c5dfc5b
changed some implementation details
AnnaPicha Oct 30, 2024
4a49b13
formatting changes
wiederm Oct 31, 2024
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4 changes: 4 additions & 0 deletions modelforge/potential/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
SAKEParameters,
SchNetParameters,
TensorNetParameters,
DimeNetParameters
)
from .processing import FromAtomToMoleculeReduction
from .representation import (
Expand All @@ -31,6 +32,7 @@
from .tensornet import TensorNetCore
from .aimnet2 import AimNet2Core
from .ani import ANI2xCore
from .dimenet import DimeNetCore


class _Implemented_NNP_Parameters(Enum):
Expand All @@ -41,6 +43,7 @@ class _Implemented_NNP_Parameters(Enum):
PHYSNET_PARAMETERS = PhysNetParameters
SAKE_PARAMETERS = SAKEParameters
AIMNET2_PARAMETERS = AimNet2Parameters
DIMENET_PARAMETERS = DimeNetParameters

@classmethod
def get_neural_network_parameter_class(cls, neural_network_name: str):
Expand All @@ -63,6 +66,7 @@ class _Implemented_NNPs(Enum):
PAINN = PaiNNCore
SAKE = SAKECore
AIMNET2 = AimNet2Core
DIMENET = DimeNetCore

@classmethod
def get_neural_network_class(cls, neural_network_name: str):
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