simplify kwargs logic for equations
This commit is contained in:
committed by
Giovanni Canali
parent
684d691b78
commit
7469543499
@@ -1,5 +1,7 @@
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"""Module for the Equation."""
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"""Module for the Equation."""
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import inspect
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from .equation_interface import EquationInterface
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from .equation_interface import EquationInterface
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@@ -25,6 +27,9 @@ class Equation(EquationInterface):
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"Expected a callable function, got "
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"Expected a callable function, got "
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f"{equation}"
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f"{equation}"
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)
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)
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# compute the signature
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sig = inspect.signature(equation)
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self.__len_sig = len(sig.parameters)
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self.__equation = equation
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self.__equation = equation
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def residual(self, input_, output_, params_=None):
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def residual(self, input_, output_, params_=None):
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@@ -41,9 +46,14 @@ class Equation(EquationInterface):
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parameters must be initialized to ``None``. Default is ``None``.
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parameters must be initialized to ``None``. Default is ``None``.
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:return: The computed residual of the equation.
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:return: The computed residual of the equation.
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:rtype: LabelTensor
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:rtype: LabelTensor
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:raises RuntimeError: If the underlying equation signature length is not
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2 (direct problem) or 3 (inverse problem).
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"""
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"""
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if params_ is None:
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if self.__len_sig == 2:
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result = self.__equation(input_, output_)
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return self.__equation(input_, output_)
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else:
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if self.__len_sig == 3:
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result = self.__equation(input_, output_, params_)
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return self.__equation(input_, output_, params_)
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return result
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raise RuntimeError(
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f"Unexpected number of arguments in equation: {self.__len_sig}. "
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"Expected either 2 (direct problem) or 3 (inverse problem)."
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)
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@@ -190,13 +190,9 @@ class PINNInterface(SupervisedSolverInterface, metaclass=ABCMeta):
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:return: The residual of the solution of the model.
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:return: The residual of the solution of the model.
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:rtype: LabelTensor
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:rtype: LabelTensor
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"""
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"""
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try:
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residual = equation.residual(
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residual = equation.residual(samples, self.forward(samples))
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samples, self.forward(samples), self._params
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except TypeError:
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)
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# this occurs when the function has three inputs (inverse problem)
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residual = equation.residual(
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samples, self.forward(samples), self._params
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)
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return residual
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return residual
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def _residual_loss(self, samples, equation):
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def _residual_loss(self, samples, equation):
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