nnrl/nn/distributions/abstract.py
def reproduce(self, value):
        """Produce a reparametrized sample with the same value as `value`."""
        if self.cond_dist is not None:
            return self.cond_dist.reproduce(value, self.params)
        return (
            torch.tensor(np.nan).float().expand_as(value),
            torch.tensor(np.nan).float().expand_as(value),
        )
Produce a reparametrized sample with the same value as `value`.
Produce a reparametrized sample with the same value as `value`.
Produce a reparametrized sample with the same value as ` value ` .
def reproduce(self, value):
        if self.cond_dist is not None:
            return self.cond_dist.reproduce(value, self.params)
        return (
            torch.tensor(np.nan).float().expand_as(value),
            torch.tensor(np.nan).float().expand_as(value),
        )
def reproduce ( self , value ) : if self . cond_dist is not None : return self . cond_dist . reproduce ( value , self . params ) return ( torch . tensor ( np . nan ) . float ( ) . expand_as ( value ) , torch . tensor ( np . nan ) . float ( ) . expand_as ( value ) , )
Produce a reparametrized sample with the same value as `value`.
Produce a reparametrized sample with the same value as ` value ` .
"""Produce a reparametrized sample with the same value as `value`."""
self
value