def __call__(self, *args):
if self.get_dim_in() is None:
self.infer_shape(*map(lambda x: T.get_shape(x)[1:], args))
if self.is_initialized():
self.initialize()
else:
raise Exception('Not enough information to initialize network')
return self.forward(*args)
def _statistic(self, stat):
weights = Stats.X(self.weights)
stats = stat(self.tensor)
out = T.core.tensordot(weights, stats, 1)
out.set_shape(T.get_shape(stats)[1:])
return out