Created
July 20, 2019 02:24
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PyTorch CSV
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from torch.utils.data import Dataset, DataLoader | |
device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
class CSVDataset(Dataset): | |
def __init__(self, x, y): | |
self.data = torch.tensor(x, dtype=torch.float, device=device) | |
self.target = torch.tensor(y, dtype=torch.long, device=device) | |
def __getitem__(self, index): | |
return self.data[index], self.target[index] | |
def __len__(self): | |
return self.data.shape[0] | |
x = (pd.read_csv('./data/AI/x', sep='\t', header=None)).values | |
y = (pd.read_csv('./data/AI/y', sep='\t', header=None)[0]).values | |
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=0) | |
train_dataset = CSVDataset(X_train, y_train) | |
test_dataset = CSVDataset(X_test, y_test) |
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