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Honor calculator dtype in GraphConverter.convert #174

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Honor calculator dtype in GraphConverter.convert #174

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17 changes: 9 additions & 8 deletions src/mattersim/datasets/utils/converter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -218,13 +218,14 @@ def convert(
atoms.set_scaled_positions(scaled_pos)
args = {}
if self.model_type == "m3gnet":
dtype = kwargs.get("dtype", torch.float32)
args["num_atoms"] = len(atoms)
args["num_nodes"] = len(atoms)
args["atom_attr"] = torch.FloatTensor(
atoms.get_atomic_numbers()
args["atom_attr"] = torch.tensor(
atoms.get_atomic_numbers(), dtype=dtype
).unsqueeze(-1)
args["atom_pos"] = torch.FloatTensor(atoms.get_positions())
args["cell"] = torch.FloatTensor(np.array(atoms.cell)).unsqueeze(0)
args["atom_pos"] = torch.tensor(atoms.get_positions(), dtype=dtype)
args["cell"] = torch.tensor(np.array(atoms.cell), dtype=dtype).unsqueeze(0)
(
sent_index,
receive_index,
Expand All @@ -235,7 +236,7 @@ def convert(
args["edge_index"] = torch.from_numpy(
np.array([sent_index, receive_index])
)
args["pbc_offsets"] = torch.FloatTensor(shift_vectors)
args["pbc_offsets"] = torch.tensor(shift_vectors, dtype=dtype)
if self.has_threebody:
(
triple_bond_index,
Expand Down Expand Up @@ -263,11 +264,11 @@ def convert(
args["num_three_body"] = None
args["num_triple_ij"] = None
if energy is not None:
args["energy"] = torch.FloatTensor([energy])
args["energy"] = torch.tensor([energy], dtype=dtype)
if forces is not None:
args["forces"] = torch.FloatTensor(forces)
args["forces"] = torch.tensor(forces, dtype=dtype)
if stress is not None:
args["stress"] = torch.FloatTensor(stress).unsqueeze(0)
args["stress"] = torch.tensor(stress, dtype=dtype).unsqueeze(0)
return M3GNetData(**args)

elif self.model_type == "graphormer":
Expand Down
1 change: 1 addition & 0 deletions src/mattersim/forcefield/potential.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1355,6 +1355,7 @@ def calculate(
cutoff=cutoff,
threebody_cutoff=threebody_cutoff,
batch_converter=self.batch_converter,
dtype=self.dtype,
**self.args_dict,
)
graph_batch = next(iter(dataloader))
Expand Down