class LWLActor(BaseActor): """Actor for training the LWL network.""" def __init__(self, net, objective, loss_weight=None, num_refinement_iter=3, disable_backbone_bn=False, disable_all_bn=False): """ args: net - The network model to train objective - Loss functions loss_weight - Weights for each training loss num_refinement_iter - Number of update iterations N^{train}_{update} used to update the target model in each frame disable_backbone_bn - If True, all batch norm layers in the backbone feature extractor are disabled, i.e. set to eval mode. disable_all_bn - If True, all the batch norm layers in network are disabled, i.e. set to eval mode. """ super().__init__(net, objective) if loss_weight is None: loss_weight = {'segm': 1.0} self.loss_weight = loss_weight self.num_refinement_iter = num_refinement_iter self.disable_backbone_bn = disable_backbone_bn self.disable_all_bn = disable_all_bn def train(self, mode=True): """ Set whether the network is in train mode. args: mode (True) - Bool specifying whether in training mode. """ self.net.train(mode)
时间: 2024-02-10 20:30:01 浏览: 95
这是一个用于训练LWL网络的Actor类。在初始化时,它接收了一些参数,包括net(模型)、objective(目标函数)、loss_weight(损失权重)、num_refinement_iter(每个帧中用于更新目标模型的更新迭代次数)、disable_backbone_bn(如果为True,则禁用骨干特征提取器中的所有批归一化层,即将其设置为eval模式)和disable_all_bn(如果为True,则禁用网络中的所有批归一化层,即将其设置为eval模式)。
在该类中,train方法用于设置网络是否处于训练模式。默认情况下,该方法将网络设置为训练模式。如果将mode参数设置为False,则可以将网络设置为评估模式。
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class KYSActor(BaseActor): """ Actor for training KYS model """ def __init__(self, net, objective, loss_weight=None, dimp_jitter_fn=None): super().__init__(net, objective) self.loss_weight = loss_weight self.dimp_jitter_fn = dimp_jitter_fn # TODO set it somewhere
根据你的代码,这是一个用于训练 KYS 模型的 Actor 类。在初始化时,它接收了一些参数,包括 net(模型)、objective(目标函数)、loss_weight(损失权重)和 dimp_jitter_fn(噪声函数)。其中,loss_weight 和 dimp_jitter_fn 都是可选的参数。在该类中,TODO 代表需要在代码中其他地方设置它。
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