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Refactoring solvers (#541)

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* Refactoring solvers

* Simplify logic compile
* Improve and update doc
* Create SupervisedSolverInterface
* Specialize SupervisedSolver and ReducedOrderModelSolver
* Create EnsembleSolverInterface + EnsembleSupervisedSolver
* Create tests ensemble solvers

* formatter

* codacy

* fix issues + speedup test
This commit is contained in:
Dario Coscia
2025-04-09 14:51:42 +02:00
parent 485c8dd789
commit 6dd7bd2825
37 changed files with 1514 additions and 510 deletions
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12
tests/test_solver/test_supervised_solver.py
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@@ -30,9 +30,9 @@ class TensorProblem(AbstractProblem):
}
x = torch.rand((100, 20, 5))
pos = torch.rand((100, 20, 2))
output_ = torch.rand((100, 20, 1))
x = torch.rand((15, 20, 5))
pos = torch.rand((15, 20, 2))
output_ = torch.rand((15, 20, 1))
input_ = [
KNNGraph(x=x_, pos=pos_, neighbours=3, edge_attr=True)
for x_, pos_ in zip(x, pos)
@@ -44,9 +44,9 @@ class GraphProblem(AbstractProblem):
conditions = {"data": Condition(input=input_, target=output_)}
x = LabelTensor(torch.rand((100, 20, 5)), ["a", "b", "c", "d", "e"])
pos = LabelTensor(torch.rand((100, 20, 2)), ["x", "y"])
output_ = LabelTensor(torch.rand((100, 20, 1)), ["u"])
x = LabelTensor(torch.rand((15, 20, 5)), ["a", "b", "c", "d", "e"])
pos = LabelTensor(torch.rand((15, 20, 2)), ["x", "y"])
output_ = LabelTensor(torch.rand((15, 20, 1)), ["u"])
input_ = [
KNNGraph(x=x[i], pos=pos[i], neighbours=3, edge_attr=True)
for i in range(len(x))