nnrl/nn/distributions/abstract.py
def icdf(self, value: torch.Tensor, params: Dict[str, torch.Tensor]):
        """Returns the inverse cumulative density/mass function evaluated at `value`."""
        if self.distribution is not None:
            return self.distribution.icdf(value)
        return torch.tensor(np.nan).float().expand_as(value)
Returns the inverse cumulative density/mass function evaluated at `value`.
Returns the inverse cumulative density/mass function evaluated at `value`.
Returns the inverse cumulative density / mass function evaluated at ` value ` .
def icdf(self, value: torch.Tensor, params: Dict[str, torch.Tensor]):
        if self.distribution is not None:
            return self.distribution.icdf(value)
        return torch.tensor(np.nan).float().expand_as(value)
def icdf ( self , value : torch . Tensor , params : Dict [ str , torch . Tensor ] ) : if self . distribution is not None : return self . distribution . icdf ( value ) return torch . tensor ( np . nan ) . float ( ) . expand_as ( value )
Returns the inverse cumulative density/mass function evaluated at `value`.
Returns the inverse cumulative density / mass function evaluated at ` value ` .
"""Returns the inverse cumulative density/mass function evaluated at `value`."""
self
value
torch.Tensor
params
Dict[str, torch.Tensor]