flowtorch.bijectors.sigmoid
class
flowtorch.bijectors.Sigmoid
Inherits from: flowtorch.bijectors.fixed.Fixedempty docstring
member
__init__
(self, params: Union[flowtorch.lazy.Lazy, NoneType] = None, *, shape: torch.Size, context_shape: Union[torch.Size, NoneType] = None) -> None<empty docstring>
member
forward
(self, x: torch.Tensor, context: Union[torch.Tensor, NoneType] = None) -> torch.Tensor<empty docstring>
member
forward_shape
(self, shape: torch.Size) -> torch.Size
Infers the shape of the forward computation, given the input shape.
Defaults to preserving shape.
member
inverse
(self, y: torch.Tensor, x: Union[torch.Tensor, NoneType] = None, context: Union[torch.Tensor, NoneType] = None) -> torch.Tensor<empty docstring>
member
inverse_shape
(self, shape: torch.Size) -> torch.Size
Infers the shapes of the inverse computation, given the output shape.
Defaults to preserving shape.
member
log_abs_det_jacobian
(self, x: torch.Tensor, y: torch.Tensor, context: Union[torch.Tensor, NoneType] = None) -> torch.Tensor
Computes the log det jacobian `log |dy/dx|` given input and output.
By default, assumes a volume preserving bijection.
member
param_shapes
(self, shape: torch.Size) -> Sequence[torch.Size]
Given a base distribution, calculate the parameters for the transformation
of that distribution under this bijector. By default, no parameters are
set.