def __init__(self, net, sens=False):
super().__init__()
self.grad = P.GradOperation(get_all=True,
get_by_list=True,
sens_param=sens)
self.net = net
self.params = ParameterTuple(self.net.trainable_params())
def __init__(self, grad, network, wrt_params=False, real_inputs_count=None):
super().__init__()
self.network = network
self.grad = grad
self.sens_param = self.grad.sens_param
self.wrt_params = wrt_params
self.real_inputs_count = real_inputs_count
if self.wrt_params:
self.params = ParameterTuple(self.network.trainable_params())
def __init__(self, func, wrt_params, params, grad_op, sens):
super(Bprop, self).__init__(auto_prefix=False)
self.func = func
self.wrt_params = wrt_params
self.params = None
if self.wrt_params and params:
self.params = ParameterTuple(params)
self.grad = grad_op
self.sens = sens
self.with_sens = False
if sens is not None:
self.with_sens = True
def __init__(self, network):
super(GetParamGrad, self).__init__(auto_prefix=False)
self.network = network
self.weights = ParameterTuple(network.trainable_params())
self.grad = C.GradOperation(get_by_list=True, sens_param=True)