def __init__(self, network, optimizer=None):
super(ModelBert, self).__init__()
self.optimizer = optimizer
manager = DynamicLossScaleManager()
update_cell = LossScaleUpdateCell(manager)
self.train_network = BertTrainOneStepWithLossScaleCell(network, self.optimizer,
scale_update_cell=update_cell)
self.train_network.set_train()
class ModelBert(nn.Cell):
def __init__(self, network, optimizer=None):
super(ModelBert, self).__init__()
self.optimizer = optimizer
self.train_network = BertTrainOneStepWithLossScaleCell(network, self.optimizer)
self.train_network.set_train()
def construct(self, arg0, arg1, arg2, arg3, arg4, arg5, arg6, arg7):
return self.train_network(arg0, arg1, arg2, arg3, arg4, arg5, arg6, arg7)
class ModelBert(nn.Cell):
def __init__(self, network, optimizer=None):
super(ModelBert, self).__init__()
self.optimizer = optimizer
manager = DynamicLossScaleManager()
update_cell = LossScaleUpdateCell(manager)
self.train_network = BertTrainOneStepWithLossScaleCell(network, self.optimizer,
scale_update_cell=update_cell)
self.train_network.set_train()
def construct(self, arg0, arg1, arg2, arg3, arg4, arg5, arg6, arg7):
return self.train_network(arg0, arg1, arg2, arg3, arg4, arg5, arg6, arg7)
def __init__(self, network, optimizer=None):
super(ModelBert, self).__init__()
self.optimizer = optimizer
self.train_network = BertTrainOneStepWithLossScaleCell(network, self.optimizer)
self.train_network.set_train()
