Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Run - Data Preparation V2
1 # %load data_preparation/v2.py
2
3 torch.manual_seed(13)
4
5 # Builds tensors from Numpy arrays BEFORE split
6 x_tensor = torch.as_tensor(x).float()
7 y_tensor = torch.as_tensor(y).float()
8
9 # Builds dataset containing ALL data points
10 dataset = TensorDataset(x_tensor, y_tensor)
11
12 # Performs the split
13 ratio = .8
14 n_total = len(dataset)
15 n_train = int(n_total * ratio)
16 n_val = n_total - n_train
17
18 train_data, val_data = random_split(dataset, [n_train, n_val])
19
20 # Builds a loader of each set
21 train_loader = DataLoader(
22 dataset=train_data,
23 batch_size=16,
24 shuffle=True
25 )
26 val_loader = DataLoader(dataset=val_data, batch_size=16)
Putting It All Together | 203