def get_monitoring_channels(self, model, data, **kwargs):
d = Cost.get_monitoring_channels(self, model, data)
if self.dropout:
self.dropout = False
d['nodrop_obj'] = self.expr(model, data, **kwargs)
self.dropout = True
return d
def get_gradients(self, model, data, unsup_aux_var=None, **kwargs):
self.get_data_specs(model)[0].validate(data)
assert unsup_aux_var is unsup_counter
called[1] = True
gradients, updates = Cost.get_gradients(self, model, data, unsup_aux_var=unsup_aux_var)
updates[grad_counter] = grad_counter + 1
return gradients, updates
def get_monitoring_channels(self, model, data, **kwargs):
d = Cost.get_monitoring_channels(self, model, data)
if self.dropout:
self.dropout = False
d['nodrop_obj'] = self.expr(model, data, **kwargs)
self.dropout = True
return d
def get_gradients(self, model, data, unsup_aux_var=None, **kwargs):
self.get_data_specs(model)[0].validate(data)
assert unsup_aux_var is unsup_counter
called[1] = True
gradients, updates = Cost.get_gradients(
self, model, data, unsup_aux_var=unsup_aux_var)
updates[grad_counter] = grad_counter + 1
return gradients, updates
def get_gradients(self,
model,
X,
Y=None,
unsup_aux_var=None,
**kwargs):
assert unsup_aux_var is unsup_counter
called[1] = True
gradients, updates = Cost.get_gradients(
self, model, X, Y, unsup_aux_var=unsup_aux_var)
updates[grad_counter] = grad_counter + 1
return gradients, updates
def get_gradients(self, model, X, Y=None, unsup_aux_var=None, **kwargs):
assert unsup_aux_var is unsup_counter
called[1] = True
gradients, updates = Cost.get_gradients(self, model, X, Y, unsup_aux_var=unsup_aux_var)
updates[grad_counter] = grad_counter + 1
return gradients, updates
