def __init__(self,
output_size: OutputSize,
mlp_input_size: Union[torch.Size, MaybeTuple[int], int],
distribution: Union[Distribution, str] = 'MultivariateNormal',
distribution_kwargs: Optional[Dict[str, Any]] = None,
hparams: Optional[HParams] = None):
super().__init__(output_size, hparams)
if distribution_kwargs is None:
distribution_kwargs = {}
self._dstr_type = distribution
self._dstr_kwargs = distribution_kwargs
for dstr_attr, dstr_val in distribution_kwargs.items():
if isinstance(dstr_val, torch.Tensor):
dstr_param = nn.Parameter(dstr_val)
distribution_kwargs[dstr_attr] = dstr_param
self.register_parameter(dstr_attr, dstr_param)
if isinstance(mlp_input_size, int):
input_feature = mlp_input_size
else:
input_feature = np.prod(mlp_input_size)
self._linear_layer = nn.Linear(
input_feature, _sum_output_size(output_size))
self._activation_fn = get_activation_fn(
self.hparams.activation_fn)
def __init__(self,
output_size: OutputSize,
mlp_input_size: Union[torch.Size, MaybeTuple[int], int],
distribution: Union[Distribution, str] = 'MultivariateNormal',
distribution_kwargs: Optional[Dict[str, Any]] = None,
hparams: Optional[HParams] = None):
super().__init__(output_size, hparams)
if distribution_kwargs is None:
distribution_kwargs = {}
self._dstr_kwargs = distribution_kwargs
if isinstance(distribution, str):
self._dstr: Distribution = utils.check_or_get_instance(
distribution, self._dstr_kwargs,
["torch.distributions", "texar.custom"])
else:
self._dstr = distribution
if self._dstr.has_rsample:
raise ValueError("Distribution should not be reparameterizable")
if isinstance(mlp_input_size, int):
input_feature = mlp_input_size
else:
input_feature = np.prod(mlp_input_size)
self._linear_layer = nn.Linear(
input_feature, _sum_output_size(output_size))
self._activation_fn = get_activation_fn(
self.hparams.activation_fn)
def __init__(self,
output_size: OutputSize,
linear_layer_dim: int,
hparams: Optional[HParams] = None):
super().__init__(output_size, hparams)
self._linear_layer = nn.Linear(
linear_layer_dim, _sum_output_size(output_size))
self._activation_fn = get_activation_fn(
self.hparams.activation_fn)