PYTHON

pyro pytorch

>>> from pyro.nn import DenseNN
>>> input_dim = 10
>>> split_dim = 6
>>> base_dist = dist.Normal(torch.zeros(input_dim), torch.ones(input_dim))
>>> param_dims = [input_dim-split_dim, input_dim-split_dim]
>>> hypernet = DenseNN(split_dim, [10*input_dim], param_dims)
>>> transform = AffineCoupling(split_dim, hypernet)
>>> pyro.module("my_transform", transform)  # doctest: +SKIP
>>> flow_dist = dist.TransformedDistribution(base_dist, [transform])
>>> flow_dist.sample()  # doctest: +SKIP