def __init__()

in scripts/models.py [0:0]

• 23 lines of code
• 7 McCabe index (conditional complexity)

    def __init__(self, in_features, out_features, task, hparams="default"):
        super().__init__()
        self.in_features = in_features
        self.out_features = out_features
        self.task = task

        # network architecture
        self.network = torch.nn.Linear(in_features, out_features)

        # loss
        if self.task == "regression":
            self.loss = torch.nn.MSELoss()
        else:
            self.loss = torch.nn.BCEWithLogitsLoss()

        # hyper-parameters
        if hparams == "default":
            self.hparams = {k: v[0] for k, v in self.HPARAMS.items()}
        elif hparams == "random":
            self.hparams = {k: v[1] for k, v in self.HPARAMS.items()}
        else:
            self.hparams = json.loads(hparams)

        # callbacks
        self.callbacks = {}
        for key in ["errors"]:
            self.callbacks[key] = {
                "train": [],
                "validation": [],
                "test": []
            }