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ndem0
2024-08-26 08:49:18 +00:00
committed by Nicola Demo
parent 62d50e2455
commit a1e041c1f0
1 changed files with 13 additions and 8 deletions
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15
pina/model/layers/orthogonal.py
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@@ -9,6 +9,7 @@ class OrthogonalBlock(torch.nn.Module):
The module takes a tensor of size [N, M] and returns a tensor of The module takes a tensor of size [N, M] and returns a tensor of
size [N, M] where the columns are orthonormal. size [N, M] where the columns are orthonormal.
""" """
def __init__(self, dim=-1): def __init__(self, dim=-1):
""" """
Initialize the OrthogonalBlock module. Initialize the OrthogonalBlock module.
@@ -30,8 +31,10 @@ class OrthogonalBlock(torch.nn.Module):
""" """
# check dim is less than all the other dimensions # check dim is less than all the other dimensions
if X.shape[self.dim] > min(X.shape): if X.shape[self.dim] > min(X.shape):
raise Warning("The dimension where to orthogonalize is greater\ raise Warning(
than the other dimensions") "The dimension where to orthogonalize is greater\
than the other dimensions"
)
result = torch.zeros_like(X) result = torch.zeros_like(X)
# normalize first basis # normalize first basis
@@ -42,9 +45,11 @@ class OrthogonalBlock(torch.nn.Module):
for i in range(1, X.shape[self.dim]): for i in range(1, X.shape[self.dim]):
v = torch.select(X, self.dim, i) v = torch.select(X, self.dim, i)
for j in range(i): for j in range(i):
v -= torch.sum(v * torch.select(result, self.dim, j), v -= torch.sum(
dim=self.dim, keepdim=True) * torch.select( v * torch.select(result, self.dim, j),
result, self.dim, j) dim=self.dim,
keepdim=True,
) * torch.select(result, self.dim, j)
result_i = torch.select(result, self.dim, i) result_i = torch.select(result, self.dim, i)
result_i += v / torch.norm(v) result_i += v / torch.norm(v)
return result return result