def __init__(
self,
n_conditionals,
n_inputs,
n_hiddens,
activation="relu",
input_order="sequential",
mode="sequential",
):
super().__init__(n_conditionals, n_inputs)
# save input arguments
self.activation = activation
self.n_conditionals = n_conditionals
self.n_inputs = n_inputs
self.n_hiddens = n_hiddens
self.mode = mode
# create network's parameters
self.degrees = create_degrees(n_inputs, n_hiddens, input_order, mode)
self.Ms, self.Mmp = create_masks(self.degrees)
self.Wx, self.Ws, self.bs, self.Wm, self.bm, self.Wp, self.bp = create_weights_conditional(
n_conditionals, n_inputs, n_hiddens, None
)
self.input_order = self.degrees[0]
self.activation_function = get_activation_function(activation)
# Output info. TODO: make these not properties of self
self.m = None
self.logp = None
# Dtype and GPU / CPU management
self.to_args = None
self.to_kwargs = None
def __init__(self,
n_inputs,
n_hiddens,
activation="relu",
input_order="sequential",
mode="sequential"):
super(GaussianMADE, self).__init__(n_inputs)
# save input arguments
self.activation = activation
self.n_inputs = n_inputs
self.n_hiddens = n_hiddens
self.mode = mode
# create network's parameters
self.degrees = create_degrees(n_inputs, n_hiddens, input_order, mode)
self.Ms, self.Mmp = create_masks(self.degrees)
self.Ws, self.bs, self.Wm, self.bm, self.Wp, self.bp = create_weights(
n_inputs, n_hiddens, None)
self.input_order = self.degrees[0]
self.activation_function = get_activation_function(activation)
# Output info
self.m = None
self.logp = None
# Dtype and GPU / CPU management
self.to_args = None
self.to_kwargs = None
def __init__(
self,
n_conditionals,
n_inputs,
n_hiddens,
n_components=10,
activation="relu",
input_order="sequential",
mode="sequential",
):
super(ConditionalMixtureMADE, self).__init__(n_conditionals, n_inputs)
# save input arguments
self.activation = activation
self.n_conditionals = n_conditionals
self.n_inputs = n_inputs
self.n_hiddens = n_hiddens
self.mode = mode
self.n_components = n_components
# create network's parameters
self.degrees = create_degrees(n_inputs, n_hiddens, input_order, mode)
self.Ms, self.Mmp = create_masks(self.degrees)
logger.debug("Mmp shape: %s", self.Mmp.shape)
(self.Wx, self.Ws, self.bs, self.Wm, self.bm, self.Wp, self.bp,
self.Wa,
self.ba) = create_weights_conditional(n_conditionals, n_inputs,
n_hiddens, n_components)
self.input_order = self.degrees[0]
# Shaping things
self.Mmp = self.Mmp.unsqueeze(2)
self.ba.data = self.ba.data.unsqueeze(0)
self.bp.data = self.bp.data.unsqueeze(0)
self.bm.data = self.bm.data.unsqueeze(0)
self.activation_function = get_activation_function(activation)
# Output info. TODO: make these not properties of self
self.m = None
self.logp = None
self.loga = None
# Dtype and GPU / CPU management
self.to_args = None
self.to_kwargs = None
