SupervisedProblem#
Formulation of a Supervised Problem in PINA.
- class SupervisedProblem(input_, output_, input_variables=None, output_variables=None)[source]#
Bases:
AbstractProblem
Definition of a supervised-learning problem.
This class provides a simple way to define a supervised problem using a single condition of type
InputTargetCondition
.- Example:
>>> import torch >>> input_data = torch.rand((100, 10)) >>> output_data = torch.rand((100, 10)) >>> problem = SupervisedProblem(input_data, output_data)
Initialization of the
SupervisedProblem
class.- Parameters:
input (torch.Tensor | LabelTensor | Graph | Data) – Input data of the problem.
output (torch.Tensor | LabelTensor | Graph | Data) – Output data of the problem.
- input_variables = None#
- output_variables = None#