def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.rate is None:
self.rate = Hypers.FlatExp(parent + 'rate', shape=self.shape)
if self.directions is None:
self.directions = Hypers.FlatExp(parent + 'directions',
shape=(self.p, self.shape))
self.hypers += [self.rate, self.directions]
def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.constant is None:
self.constant = Hypers.Flat(parent + self.name + '_Constant')
if self.coeff is None:
self.coeff = Hypers.Flat(parent + self.name + '_Coeff',
shape=self.shape)
self.hypers += [self.constant, self.coeff]
def check_hypers(self, parent=''):
if self.shift is None:
self.shift = Hypers.Flat(parent + self.name + '_shift')
if self.scale is None:
self.scale = Hypers.FlatExp(parent + self.name + '_scale')
if self.power is None:
self.power = Hypers.FlatExp(parent + self.name + '_power')
self.hypers += [self.shift, self.scale, self.power]
def check_hypers(self, parent=''):
if self.a is None:
self.a = Hypers.FlatExp(parent + self.name + '_a', shape=self.n)
if self.b is None:
self.b = Hypers.FlatExp(parent + self.name + '_b', shape=self.n)
if self.c is None:
self.c = Hypers.Flat(parent + self.name + '_c', shape=self.n)
self.hypers += [self.a, self.b, self.c]
def check_hypers(self, parent=''):
if self.shift is None:
self.shift = Hypers.FlatExp(parent + self.name + '_shift',
shape=self.n)
if self.power is None:
self.power = Hypers.FlatExp(parent + self.name + '_power',
shape=self.n)
if self.w is None:
self.w = Hypers.FlatExp(parent + self.name + '_w', shape=self.n)
self.hypers += [self.shift, self.power, self.w]
def check_hypers(self, parent=''):
if self.lower is None:
self.lower = Hypers.Flat(parent + self.name + '_lower')
if self.high is None:
self.high = Hypers.FlatExp(parent + self.name + '_high')
if self.location is None:
self.location = Hypers.Flat(parent + self.name + '_location')
if self.scale is None:
self.scale = Hypers.FlatExp(parent + self.name + '_scale')
self.hypers += [self.lower, self.high, self.location, self.scale]
def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.freq is None:
self.freq = Hypers.FlatExp(parent + self.name + '_freq',
shape=self.shape)
if self.rate is None:
self.rate = Hypers.FlatExp(parent + self.name + '_rate',
shape=self.shape)
if isinstance(self.rate, tt.TensorVariable):
self.hypers += [self.rate]
if isinstance(self.freq, tt.TensorVariable):
self.hypers += [self.freq]
def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.rate is None:
self.rate = Hypers.FlatExp(parent + 'rate', shape=self.shape)
self.hypers += [self.rate]
def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.bias is None:
self.bias = Hypers.FlatExp(parent + 'bias')
self.hypers += [self.bias]
def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.bias is None:
self.bias = Hypers.Flat(parent + self.name + '_Bias')
self.hypers += [self.bias]
def check_hypers(self, parent=''):
if self.shift is None:
self.shift = Hypers.Flat(parent + self.name + '_shift')
self.hypers += [self.shift]
def check_hypers(self, parent=''):
super().check_hypers(parent=parent)
if self.alpha is None:
self.alpha = Hypers.FlatExp(parent + self.name + '_alpha')
self.hypers += [self.alpha]
def check_hypers(self, parent=''):
if self.var is None:
self.var = Hypers.FlatExp(parent + self.name + '_var')
if isinstance(self.var, tt.TensorVariable):
self.hypers += [self.var]
self.metric.check_hypers(parent + self.name + '_')