小编Cyb*_*iot的帖子

我正在研究带有数字的经典示例。我想创建我的第一个神经网络来预测数字图像 {0,1,2,3,4,5,6,7,8,9} 的标签。所以第一列train.txt有标签，所有其他列是每个标签的特征。我定义了一个类来导入我的数据：

class DigitDataset(Dataset):
    """Digit dataset."""

    def __init__(self, file_path, transform=None):
        """
        Args:
            csv_file (string): Path to the csv file with annotations.
            root_dir (string): Directory with all the images.
            transform (callable, optional): Optional transform to be applied
                on a sample.
        """
        self.data = pd.read_csv(file_path, header = None, sep =" ")
        self.transform = transform

    def __len__(self):
        return len(self.data)

    def __getitem__(self, idx):
        if torch.is_tensor(idx):
            idx = idx.tolist()

        labels = self.data.iloc[idx,0]
        images = self.data.iloc[idx,1:-1].values.astype(np.uint8).reshape((1,16,16))

        if self.transform is not None:
            sample = …