def __init__(self, x_dim, z_dim, h_dim=512):
super(Discriminator_2, self).__init__()
self.h_dim = h_dim
with self.init_scope():
self.l1 = L.Linear(x_dim + z_dim,
h_dim,
initialW=xavier.Xavier(x_dim + z_dim, h_dim))
self.l2 = L.Linear(h_dim,
h_dim,
initialW=xavier.Xavier(h_dim, h_dim))
self.l3 = L.Linear(h_dim, 1, initialW=xavier.Xavier(h_dim, 1))
def __init__(self, x_dim, eps_dim, h_dim=512):
super(Encoder_4, self).__init__()
with self.init_scope():
self.l1 = L.Linear(x_dim + eps_dim,
h_dim,
initialW=xavier.Xavier(x_dim + eps_dim, h_dim))
self.l2 = L.Linear(h_dim,
h_dim,
initialW=xavier.Xavier(h_dim, h_dim))
self.l3 = L.Linear(h_dim,
eps_dim,
initialW=xavier.Xavier(h_dim, eps_dim))
def __init__(self, z_dim, x_dim=1, h_dim=512):
super(Decoder_2, self).__init__()
with self.init_scope():
self.l1 = L.Linear(z_dim,
h_dim,
initialW=xavier.Xavier(z_dim, h_dim))
self.l2 = L.Linear(h_dim,
h_dim,
initialW=xavier.Xavier(h_dim, h_dim))
self.l3 = L.Linear(h_dim,
x_dim,
initialW=xavier.Xavier(h_dim, x_dim))
def __init__(self, n_in, n_latent, n_h, activation=F.tanh):
super(VAE, self).__init__()
self.activation = activation
with self.init_scope():
# encoder
self.le1 = L.Linear(n_in, n_h, initialW=xavier.Xavier(n_in, n_h))
self.le2 = L.Linear(n_h, n_h, initialW=xavier.Xavier(n_h, n_h))
self.le3_mu = L.Linear(n_h,
n_latent,
initialW=xavier.Xavier(n_h, n_latent))
self.le3_ln_var = L.Linear(n_h,
n_latent,
initialW=xavier.Xavier(n_h, n_latent))
# decoder
self.ld1 = L.Linear(n_latent,
n_h,
initialW=xavier.Xavier(n_latent, n_h))
self.ld2 = L.Linear(n_h, n_h, initialW=xavier.Xavier(n_h, n_h))
self.ld3_mu = L.Linear(n_h,
n_in,
initialW=xavier.Xavier(n_h, n_in))
self.ld3_ln_var = L.Linear(n_h,
n_in,
initialW=xavier.Xavier(n_h, n_in))
def __init__(self, x_dim, eps_dim, h_dim=512):
super(Encoder_1, self).__init__()
with self.init_scope():
self.a1 = L.Linear(eps_dim,
x_dim,
initialW=xavier.Xavier(eps_dim, x_dim))
self.a2 = L.Linear(eps_dim,
h_dim,
initialW=xavier.Xavier(eps_dim, h_dim))
self.a3 = L.Linear(eps_dim,
h_dim,
initialW=xavier.Xavier(eps_dim, h_dim))
self.l1 = L.Linear(x_dim,
h_dim,
initialW=xavier.Xavier(eps_dim, h_dim))
self.l2 = L.Linear(h_dim,
h_dim,
initialW=xavier.Xavier(h_dim, h_dim))
self.l3 = L.Linear(
h_dim,
eps_dim,
initialW=chainer.initializers.Normal(scale=1e-5))