Fix bugs in DataLoader and tutorial5 notebook #376
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FilippoOlivo
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…rst attempt with PINN
…__torch_functions__ and __mul__
dario-coscia
requested changes
Nov 11, 2024
| @@ -53,11 +55,20 @@ def __init__( | |||
| :param torch.nn.Module loss: The loss function used as minimizer, | |||
| default :class:`torch.nn.MSELoss`. | |||
| """ | |||
| if optimizers is None: | |||
| optimizers = TorchOptimizer(torch.optim.Adam, lr=0.001) | |||
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why are you not passing kwargs?
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kwargs are passed when TorchOptimizer is initialized outside the Solver class
from pina.optim import TorchOptimizer
from pina.solver import PINN
from torch.optim import SGD
optimizer = TorchOptimizer(SGD, lr=0.1, ...)
in_ = LabelTensor(torch.rand((10,2)), ['u_0', 'u_1'])
out_ = LabelTensor(torch.rand((10,1)), ['u'])
class TestProblem(AbstractProblem):
input_variables = ['u_0', 'u_1']
output_variables = ['u']
conditions = {
'data': Condition(input_points=in_, output_points=out_),
}
solver = SupervisedSolver(problem=problem, model=model, optimizer=optimizer)
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Can we pass the standard torch optimizer and inside solvers do the wrapper? To me, for the user, this is more intuitive
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@ndem0 what do you think?
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…LabelParameter class (equivalent of LabelTensor for torch.nn.Parameters)
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