Expand the line

1 
class NetDataset(Dataset):

    def __init__(self):
        xy = np.loadtxt('data_2d.txt', delimiter=';', dtype=np.float32)
        self.len = xy.shape[0]
        self.x_data = torch.from_numpy(xy[:, 0:-1])
        self.y_data = torch.from_numpy(xy[:, [-1]])

    def __getitem__(self, index):
        return self.x_data[index], self.y_data[index]

    def __len__(self):
        return self.len

self.x_data = torch.from_numpy(xy[:, 0:-1])
it gives me the following view [0.1 0.4 0.5 0.2 0.8 0.5]

How can i get this [[0.1 0.4 0.5][0.2 0.8 0.5]]?

2

Hi,
What is xy[:, 0:-1] supposed to do?
Also xy[:, [-1]]?

3 
dataset = NetDataset()
train_loader = DataLoader(dataset=dataset, batch_size=128, shuffle=True)

…

for i, (inputs, labels) in enumerate(train_loader):
y_pred = model(inputs)
loss = criterion(y_pred, labels)
4

I am currently using nn.linear. I want to use nn.gru [[0.1 0.4 0.5][0.2 0.8 0.5]] - the sequence is 2

5

Sorry, what I meant was,
What do you expect xy to be here?
And what do you expect xy[:, 0:-1] to give you?
I am not familiar with such notation.