def __init__()

in src/trainer.py [0:0]

• 22 lines of code
• 2 McCabe index (conditional complexity)

    def __init__(self, config, net, dataset):
        '''
        :param config: a dict containing parameters
        :param net: the network to be trained, must be of type src.utils.Net
        :param dataset: the dataset to be trained on
        '''
        self.config = config
        self.dataset = dataset
        self.dataloader = DataLoader(dataset, batch_size=config["batch_size"], shuffle=True, num_workers=1)
        gpus = [i for i in range(config["num_gpus"])]
        self.net = th.nn.DataParallel(net, gpus)
        weights = filter(lambda x: x.requires_grad, net.parameters())
        self.optimizer = NewbobAdam(weights,
                                    net,
                                    artifacts_dir=config["artifacts_dir"],
                                    initial_learning_rate=config["learning_rate"],
                                    decay=config["newbob_decay"],
                                    max_decay=config["newbob_max_decay"])
        self.l2_loss = L2Loss(mask_beginning=config["mask_beginning"])
        self.phase_loss = PhaseLoss(sample_rate=48000, mask_beginning=config["mask_beginning"])
        self.total_iters = 0
        # switch to training mode
        self.net.train()