def setup(self, stage: str = None): df = pd.read_csv(f"{pathlib.Path(__file__).parent.absolute()}/{DATA_FILENAME}") # Split features, targets x = df.drop(columns=[Y_LABEL]).values y = df[Y_LABEL].values UCIDataModule.setup(self, x, y)
def setup(self, stage: str = None): df = pd.read_csv( f"{pathlib.Path(__file__).parent.absolute()}/{DATA_FILENAME}", sep=";") x = df.drop(columns=Y_LABEL).values y = df[Y_LABEL].values UCIDataModule.setup(self, x, y)
def setup(self, stage: str = None): df = pd.read_csv(f"{pathlib.Path(__file__).parent.absolute()}/{DATA_FILENAME}") # Loads rows as string data = np.empty((len(df.index), self.dims + self.out_dims)) for i in range(data.shape[0]): data[i] = np.array( [float(el) for el in df.values[i][0].split(" ") if el != ""] ) x = data[:, :-1] y = data[:, -1] UCIDataModule.setup(self, x, y)
def __init__( self, batch_size: int, n_workers: int, train_val_split: float = 0.9, test_split: float = 0.1, **kwargs, ): UCIDataModule.__init__( self, batch_size, n_workers, train_val_split, test_split, ) # Manual as we know it self.dims = 4 self.out_dims = 1