def __init__(self,
dim,
hid_dim,
context_dim,
num_layers,
activation=nn.ELU(),
fixed_order=False,
num_ds_dim=4,
num_ds_layers=1,
num_ds_multiplier=3):
super(IAF_DSF, self).__init__()
self.dim = dim
self.context_dim = context_dim
self.num_ds_dim = num_ds_dim
self.num_ds_layers = num_ds_layers
if type(dim) is int:
self.mdl = iaf_modules.cMADE(
dim, hid_dim, context_dim, num_layers,
num_ds_multiplier * (hid_dim // dim) * num_ds_layers,
activation, fixed_order)
self.out_to_dsparams = nn.Conv1d(
num_ds_multiplier * (hid_dim // dim) * num_ds_layers,
3 * num_ds_layers * num_ds_dim, 1)
self.reset_parameters()
self.sf = SigmoidFlow(num_ds_dim)
def __init__(self, dim, hid_dim, context_dim, num_layers,
activation=nn.ELU(), realify=nn_.sigmoid, fixed_order=False):
super(IAF, self).__init__()
self.realify = realify
self.dim = dim
self.context_dim = context_dim
if type(dim) is int:
self.mdl = iaf_modules.cMADE(
dim, hid_dim, context_dim, num_layers, 2,
activation, fixed_order)
self.reset_parameters()
def __init__(self,
dim,
hid_dim,
context_dim,
num_layers,
activation=nn.ELU(),
fixed_order=False,
num_ds_dim=4,
num_ds_layers=1,
num_ds_multiplier=3):
super(IAF_DDSF, self).__init__()
self.dim = dim
self.context_dim = context_dim
self.num_ds_dim = num_ds_dim
self.num_ds_layers = num_ds_layers
if type(dim) is int:
self.mdl = iaf_modules.cMADE(
dim, hid_dim, context_dim, num_layers,
num_ds_multiplier * (hid_dim / dim) * num_ds_layers,
activation, fixed_order)
num_dsparams = 0
for i in range(num_ds_layers):
if i == 0:
in_dim = 1
else:
in_dim = num_ds_dim
if i == num_ds_layers - 1:
out_dim = 1
else:
out_dim = num_ds_dim
u_dim = in_dim
w_dim = num_ds_dim
a_dim = b_dim = num_ds_dim
num_dsparams += u_dim + w_dim + a_dim + b_dim
self.add_module('sf{}'.format(i),
DenseSigmoidFlow(in_dim, num_ds_dim, out_dim))
if type(dim) is int:
self.out_to_dsparams = nn.Conv1d(
num_ds_multiplier * (hid_dim / dim) * num_ds_layers,
num_dsparams, 1)
else:
self.out_to_dsparams = nn.Conv1d(
num_ds_multiplier * (hid_dim / dim[0]) * num_ds_layers,
num_dsparams, 1)
self.reset_parameters()
def __init__(self,
dim,
hid_dim,
context_dim,
num_layers,
activation=nn.ELU(),
fixed_order=True):
super(IAF_VP, self).__init__()
self.dim = dim
self.context_dim = context_dim
if type(dim) is int:
self.mdl = iaf_modules.cMADE(dim, hid_dim, context_dim, num_layers,
1, activation, fixed_order)
self.reset_parameters()
