def _get_dist_params(self, x: torch.Tensor) -> Tuple[(torch.FloatTensor, torch.FloatTensor)]:
    'Returns the learned paremters of the distribution.\n\n        Parameters\n        ----------\n        x : torch.FloatTensor\n            Input state tensor.\n\n        Returns\n        -------\n        Tuple[torch.FloatTensor, torch.FloatTensor, torch.FloatTensor]\n            Distribution mean (mu), Distribution standard deviation (sigma), State value estimate (V_hat).\n        '
    x = self.trunk(x)
    V_hat = self.value_head(x)
    pi_logits = self.dist_head(x)
    return (pi_logits, V_hat)
Returns the learned paremters of the distribution.

Parameters
----------
x : torch.FloatTensor
    Input state tensor.

Returns
-------
Tuple[torch.FloatTensor, torch.FloatTensor, torch.FloatTensor]
    Distribution mean (mu), Distribution standard deviation (sigma), State value estimate (V_hat).
def _get_dist_params(self, x: torch.Tensor) -> Tuple[(torch.FloatTensor, torch.FloatTensor)]:
    'Returns the learned paremters of the distribution.\n\n        Parameters\n        ----------\n        x : torch.FloatTensor\n            Input state tensor.\n\n        Returns\n        -------\n        Tuple[torch.FloatTensor, torch.FloatTensor, torch.FloatTensor]\n            Distribution mean (mu), Distribution standard deviation (sigma), State value estimate (V_hat).\n        '
    x = self.trunk(x)
    V_hat = self.value_head(x)
    pi_logits = self.dist_head(x)
    return (pi_logits, V_hat)