latent_size = 20
encoder = ConditionalNormal(MLP(3000, latent_size,
hidden_units=[512,256],
activation=‘relu’,
in_lambda=lambda x:  x.view(x.shape[0], 3000).float() - 1))
decoder = ConditionalNormal(MLP(latent_size, 3000,
hidden_units=[512,256],
activation=‘relu’,
out_lambda=lambda x:  x.view(x.shape[0], 3000).float() - 1))
model = Flow(base_dist=StandardNormal((latent_size,)),
transforms=[
VAE(encoder=encoder, decoder=decoder)
]).to(device)