dagma.nonlinear.DagmaNonlinear¶

class dagma.nonlinear.DagmaNonlinear(model: torch.nn.Module, verbose: bool = False, dtype: torch.dtype = torch.double)¶

Class that implements the DAGMA algorithm

Parameters:¶

model : nn.Module¶

Neural net that models the structural equations.

verbose : bool, optional¶

If true, the loss/score and h values will print to stdout every checkpoint iterations, as defined in fit(). Defaults to False.

dtype : torch.dtype, optional¶

float number precision, by default torch.double.

Methods¶

log_mse_loss(→ torch.Tensor)	Computes the logarithm of the MSE loss:
minimize(→ bool)	Solves the optimization problem:
fit(→ numpy.ndarray)	Runs the DAGMA algorithm and fits the model to the dataset.